date: 2013-08
title: Highlights From the Latest in Diabetes Research

# The Relationship Between Obesity and Vitamin D Deficiency: Causation Determined?

Multiple investigations have evaluated the relationship between obesity and vitamin D deficiency, two modifiable factors that contribute to the risk of several chronic diseases. While such studies have identified a strong association between these phenotypes, it has been difficult to determine causality and the direction of the association. Through a series of sophisticated genetic analyses including bi-directional Mendelian randomization (MR), results from Vimaleswaran et al. have highlighted potentially important insights regarding the link between obesity, as assessed by BMI, and vitamin D deficiency. Using meta-analysis approaches in approximately 42,000 participants of D-CarDia, the authors observed that each unit increase in BMI was associated with a 1.15% decrease in 25-hydroxyvitamin D \[25(OH)D\]. In order to infer causality, their findings were extended by MR using previously established BMI-related (*n* = 12) and vitamin D–related (*n* = 4) single nucleotide polymorphisms in order to generate allele scores for the analyses. These analyses revealed that while the BMI allele score was significantly associated with reduced 25(OH)D levels (-0.06% \[95% CI -0.10 to -0.02%\], *P* = 0.004), neither the vitamin D synthesis or metabolism allele scores were associated with BMI (0.01 \[-0.17 to 0.20\], *P* = 0.88 and 0.17 \[-0.02 to 0.35\], *P* = 0.08, respectively). Using the instrumental variable (IV) ratio method, it was observed that each 10% increase in BMI led to a 4.2% decrease in 25(OH)D levels. In contrast, IV analyses did not provide evidence that 25(OH)D levels significantly affected BMI. Follow-up analyses using data from the Genetic Investigation of Anthropometric Traits (GIANT) consortium confirmed the lack of association between vitamin D allele scores and BMI. Together, these results suggest that an increase in obesity results in lower vitamin D status but that vitamin D concentration has little or no impact on the development of obesity. — *Joshua P. Lewis, PhD*

**Vimaleswaran et al. Causal relationship between obesity and vitamin D status: bi-directional Mendelian randomization analysis of multiple cohorts. PLoS Med 2013;10:e1001383**

# Defective Insulin Signaling: A Common Feature of Diabetes and Alzheimer's Disease?

Obesity and aging are at the root of considerable public health concern in many developed countries: In many industrialized nations, there has been a marked increase in the prevalence of obesity over the last several decades, a trend that is occurring in tandem with the "graying" of many of the same populations. The prevalence of type 2 diabetes has increased in parallel with trends in obesity; a similar pattern is occurring for both mild cognitive impairment and Alzheimer's disease (AD) in relation to the growing number of older adults in many developed countries. There has been some research from Bomfin et al. suggesting a link between diabetes and decrements in cognition, including AD. Insulin resistance (IR) is a cardinal feature of type 2 diabetes, and there is evidence supporting the idea that IR is present in AD. Findings from recent studies suggesting that brain insulin signaling is defective in AD raise obvious questions regarding the possibility that insulin signaling defects may play a role in the development of both diabetes and AD. Building on the findings showing that amyloid-β peptide (Aβ) oligomers (AβOs) (synaptotoxins that collect in the AD brain) result in the loss of insulin receptors from neuronal tissues, new data suggest that AβOs also activate the Jun NH~2~-terminal kinase/tumor necrosis factor-α (JNK/TNF-α) pathway and induce insulin receptor substrate (IRS)-1 phosphorylation in hippocampal neurons. Both JNK activation and IRS-1 phosphorylation are also observed in diabetes, indicating that pathologic mechanisms related to insulin signaling may be shared in the two conditions. The neuronal pathologies that were induced by AβOs in these experiments were prevented with exenatide. In Tg mice with a brain condition that models AD, exenatide blocked defective insulin signaling and improved cognition. Assuming that impaired insulin signaling is in the causal pathway for AD, exploration of the role of glucagon-like peptide 1 receptors may be ripe for future investigation. It is interesting to consider the idea that two of the most pressing chronic conditions affecting developed nations could be treated with the same therapeutic agent. Despite these intriguing results, it should be stressed that the new findings could merely reflect an association of two common diseases. — *Helaine E. Resnick, PhD, MPH*

**Bomfin et al. An anti-diabetes agent protects the mouse brain from defective insulin signaling caused by Alzheimer's disease–associated Aβ oligomers. J Clin Invest 2012;122:1339–1353**

# Betatropin: A New Hormone Regulating β-Cell Replication and Mass

Although the defects underpinning type 1 and type 2 diabetes differ in fundamental ways, both conditions benefit from treatments that result in increased β-cell mass. Although there is a rapid increase in β-cell replication in the embryonic and neonatal stages of development, the rate of increase slows substantially in later life. However, the rate of β-cell replication can increase in response to certain challenges in late life, including gestation, pancreatic injury, and insulin resistance. The fact that both β-cell number and mass can increase in response to certain challenges raises the possibility to harness and direct mechanisms that favor β-cell proliferation in a manner that could have therapeutic implications. Although focusing on circulating factors is an appealing approach to this problem, targeting currently identified hormones is limited by the lack of specificity of these factors or their modest impact on β-cell proliferation. New work by Yi et al. provides intriguing data on a newly identified hormone that has potential therapeutic implications. In a series of experiments using a new mouse model in which β-cell replication can be induced, the investigators identified a gene that encodes a protein that is expressed in liver and fat. Importantly, this protein was found to be elevated in insulin resistance and to specifically induce pancreatic β-cell proliferation and increased β-cell mass. In addition to demonstrating its impact on β-cell mass, the newly published results indicate that insulin-resistant mice expressing the new protein experienced significant improvements in glucose tolerance. The investigators named this new hormone betatrophin. Although its mechanism of action remains unknown, the authors suggest that in the future, this hormone could serve as a companion to existing diabetes therapies or perhaps even replace the need for exogenous insulin. — *Helaine E. Resnick, PhD, MPH*

**Yi et al. Betatrophin: a hormone that controls pancreatic β cell proliferation. Cell 2013;153:747–758**

# New Loci Associated With Birth Weight Identify Genetic Links Between Intrauterine Growth and Adult Height and Metabolism

Fetal growth and birth weight are associated with the development of adult-onset metabolic diseases. Both environmental insults (i.e., maternal nutrition, smoking, and drug use) and genetic factors have been implicated in alterations in intrauterine growth and development. A recent report by Horikoshi et al. investigates the genetic factors affecting birth weight through an expanded meta-analysis genome-wide association study (GWAS) aimed at identifying genetic loci that also correspond with adult height and metabolic traits. The expanded meta-analysis GWAS of birth weight (26,836 subjects of European descent from 18 studies) identified four new loci associated with birth weight and confirmed three previously identified loci. Single nucleotide polymorphisms in genes in two of the loci, *ADCY5* and *CDKAL1*, were previously shown to be associated with type 2 diabetes. At both loci, the alleles associated with lower birth weight were also associated with increased risk for type 2 diabetes, with evidence for impaired insulin secretion in the adult population. These results are consistent with a reduction in birth weight due to reduced insulin concentration, which manifests as type 2 diabetes in adulthood. The Gly389-encoding allele of a missense mutation in the *ADRB1* locus (Arg389Gly) was associated with lower birth weight and lower systolic blood pressure in adulthood. Finally, the birth weight–lowering alleles at two of the birth weight–associated loci, *HMGA2* and *LCORL*, were also associated with lower adult height. This study not only identifies genetic links between intrauterine growth and adult height and metabolism, it also sheds new light on the biological pathways and mechanisms influencing these traits and development of disease. Dissecting these biological pathways and the relationships between the intrauterine and adult presentation of disease will allow for early, personalized prevention and treatment. — *Coleen M. Damcott, PhD*

**Horikoshi et al. New loci associated with birth weight identify genetic links between intrauterine growth and adult height and metabolism. Nat Genet 2013;45:76–82**


date: 2018
title: More than 90% of the world's children breathe toxic air every day

**29 October 2018 News Release Geneva** - Every day around 93% of the world's children under the age of 15 years (1.8 billion children) breathe air that is so polluted it puts their health and development at serious risk. Tragically, many of them die: WHO estimates that in 2016, 600,000 children died from acute lower respiratory infections caused by polluted air.

A new WHO report on Air pollution and child health: Prescribing clean air examines the heavy toll of both ambient (outside) and household air pollution on the health of the world's children, particularly in low- and middle-income countries. The report is being launched on the eve of WHO's first ever Global Conference on Air Pollution and Health.

It reveals that when pregnant women are exposed to polluted air, they are more likely to give birth prematurely, and have small, low birth-weight children. Air pollution also impacts neurodevelopment and cognitive ability and can trigger asthma, and childhood cancer. Children who have been exposed to high levels of air pollution may be at greater risk for chronic diseases such as cardiovascular disease later in life.

"Polluted air is poisoning millions of children and ruining their lives," says Dr Tedros Adhanom Ghebreyesus, WHO Director-General. "This is inexcusable. Every child should be able to breathe clean air so they can grow and fulfil their full potential."

One reason why children are particularly vulnerable to the effects of air pollution is that they breathe more rapidly than adults and so absorb more pollutants.

They also live closer to the ground, where some pollutants reach peak concentrations – at a time when their brains and bodies are still developing.

Newborns and young children are also more susceptible to household air pollution in homes that regularly use polluting fuels and technologies for cooking, heating and lighting

"Air Pollution is stunting our children's brains, affecting their health in more ways than we suspected. But there are many straight-forward ways to reduce emissions of dangerous pollutants," says Dr Maria Neira, Director, Department of Public Health, Environmental and Social Determinants of Health at WHO.

"WHO is supporting implementation of health-wise policy measures like accelerating the switch to clean cooking and heating fuels and technologies, promoting the use of cleaner transport, energy-efficient housing and urban planning. We are preparing the ground for low emission power generation, cleaner, safer industrial technologies and better municipal waste management, " she added.

# Key findings

-   Air pollution affects neurodevelopment, leading to lower cognitive test outcomes, negatively affecting mental and motor development.

-   Air pollution is damaging children's lung function, even at lower levels of exposures

-   Globally, 93% of the world's children under 15 years of age are exposed to ambient fine particulate matter (PM2.5) levels above WHO air quality guidelines, which include the 630 million of children under 5 years of age, and 1.8 billion of children under 15 years

-   In low- and middle-income countries around the world, 98% of all children under 5 are exposed to PM2.5 levels above WHO air quality guidelines. In comparison, in high-income countries, 52% of children under 5 are exposed to levels above WHO air quality guidelines.

-   More than 40% of the world's population – which includes 1 billion children under 15 - is exposed to high levels of household air pollution from mainly cooking with polluting technologies and fuels.

-   About 600'000 deaths in children under 15 years of age were attributed to the joint effects of ambient and household air pollution in 2016.

-   Together, household air pollution from cooking and ambient (outside) air pollution cause more than 50% of acute lower respiratory infections in children under 5 years of age in low- and middle-income countries.

-   Air pollution is one of the leading threats to child health, accounting for almost 1 in 10 deaths in children under five years of age.

WHO's First Global Conference on Air Pollution and Health, which opens in Geneva on Tuesday 30 October will provide the opportunity for world leaders; ministers of health, energy, and environment; mayors; heads of intergovernmental organizations; scientists and others to commit to act against this serious health threat, which shortens the lives of around 7 million people each year. Actions should include:

-   Action by the health sector to inform, educate, provide resources to health professionals, and engage in inter-sectoral policy making.

-   Implementation of policies to reduce air pollution: All countries should work towards meeting WHO global air quality guidelines to enhance the health and safety of children. To achieve this, governments should adopt such measures as reducing the over-dependence on fossil fuels in the global energy mix, investing in improvements in energy efficiency and facilitating the uptake of renewable energy sources. Better waste management can reduce the amount of waste that is burned within communities and thereby reducing 'community air pollution'. The exclusive use of clean technologies and fuels for household cooking, heating and lighting activities can drastically improve the air quality within homes and in the surrounding community.

-   Steps to minimize children's exposure to polluted air: Schools and playgrounds should be located away from major sources of air pollution like busy roads, factories and power plants.

Available from: <http://www.who.int/news-room/detail/29-10-2018-more-than-90-of-the-world%E2%80%99s-children-breathe-toxic-air-every-day>


abstract: A report on the conference 'Systems Genomics 2008', Heidelberg, Germany, 2-3 May 2008.
author: Rainer Pepperkok; Stefan Wiemann
date: 2008
institute: 1Cell Biology and Cell Biophysics Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany; 2Division of Molecular Genome Analysis, German Cancer Research Center, Im Neuenheimer Feld 580, 69120 Heidelberg, Germany
title: Integrating systems biology with clinical research

High-throughput techniques in genomics, proteomics, and cell biology hold the promise of systems-level analyses to elucidate fundamental biological principles and to understand and predict the behavior of cellular systems in health and disease. With this challenge in mind, the recent Systems Genomics 2008 conference <http://www.dkfz.de/mga/SG2008> in Heidelberg brought together researchers in the fields of genomics, functional genomics, and systems biology to discuss the latest technological developments and their possible implications for clinical research.

# Systems and biological networks

Two keynote presentations dealt with the understanding of interaction networks, and with the implications of such knowledge for developing new therapeutic strategies in cancer. Peter Sorger (Harvard Medical School, Boston, USA) highlighted the central role of stochastic processes in the fate of cells and of the importance of determining them quantitatively. He and his colleagues have shown that, even in a visually homogeneous cell population, not all cells react the same way in response to a specific perturbation. While the causes of such an effect are complicated enough for binary decisions like apoptosis, differentiation or cell division, they will be even more so for continuous events such as signaling and cell migration. Such processes need to be quantitatively analyzed at single-cell resolution - by live-cell imaging or flow cytometry, for example. Neither genomics nor proteomics approaches can be carried out at this level of resolution yet.

Yossi Yarden (Weizmann Institute of Science, Rehovot, Israel) discussed the robustness of biological systems as one prerequisite for cell survival in an unfriendly environment.

Taking the ErbB family of growth factor receptors and breast cancer as an example, he showed that such systems have evolved to withstand perturbations such as those induced by common therapies. He suggested that compensatory pathways provide the plasticity needed to confer drug resistance, and that this would be responsible for the long-term failure of many therapies. However, despite the fitness of cells to deal with such common perturbations, he claimed that unusual types of perturbations would render the system fragile and should re-establish drug potency. For example, targeting of ErbB2 with two different antibodies should more efficiently attract natural killer cells to the tumor cells, and combination of chemotherapy with monoclonal antibodies would better remove this receptor from the cell surface and result in reduced signaling. Cancer cells should then not be able to compensate for such uncommon perturbations, resulting in a much enhanced therapeutic response. A detailed knowledge of the signaling pathways and networks involved would define the optimal treatment regime, depending on the status of the cancer cell in terms of key signaling factors.

# High-throughput technologies

Much of our current knowledge about genes and their expression is based on the approximately 7 million expressed sequence tag (EST) sequences in the UniGene database. Sumio Sugano (University of Tokyo, Japan) introduced the next-generation DNA sequencers, such as those marketed by Illumina, ABI, and Roche, which promise to determine more than 10 million sequences from just one experiment. With this remarkable technology, genes, promoters and transcription start sites will in future be able to be mapped in single cell types with unprecedented precision. Sugano showed the preliminary results of such an unbiased approach, where an Illumina sequencer had been used to map transcription start sites and transcripts. He concluded that some start sites are indeed cell-type specific and that the huge number of tags generated permits fine-grained analysis of gene expression. But in every million cDNAs captured and sequenced by these techniques, gene expression turns out to range from a few transcripts to thousands of transcripts from the same gene. Sugano pointed out that with the depth of data achievable with next-generation sequencing, sparse transcription cannot be distinguished from what could be termed 'transcriptional noise'. There are no clear cutoffs, which complicates the detection of rarely expressed genes, and especially of intergenic and antisense transcription.

Caroline Shamu (Harvard Medical School, Boston, USA) discussed the many challenges associated with currently fashionable genome-scale screening by RNA interference (RNAi) using small interfering RNAs (siRNAs). She reported on projects where high-throughput transfection methods such as reverse transfection are combined with a conventional plate-and-assay design and high-content read-out to conduct more than 20 large-scale primary screens in different human and mouse cell lines. In her talk she concentrated on technical issues of RNAi screening in her central facility, stressing the importance of spending enough effort to make the assay robust, and to work on plate designs in order to circumvent edge and plate effects as these hamper data analysis. Once these issues are addressed, RNAi seems to be rather robust, as she screened for phenotypes in cancer, infectious diseases, neurobiology, and stem-cell biology, utilizing a number of different cell lines in combination with diverse transfection reagents and siRNA concentrations. While initial RNAi screens had mostly been done with plate readers, data acquisition is increasingly shifting towards high-content screening microscopy. Dorit Arlt (German Cancer Research Center, Heidelberg, Germany) reported that RNAi is also ideal for identifying functional interaction networks of genes. She presented data where knock-down of a single network component did not have a phenotype itself, yet the parallel perturbation of two or more genes did, thus revealing their functional interactions with the network. First she established a literature network of cell-cycle regulation consisting of the ErbB receptor family, AKT1 and MEK1 signaling intermediates, estrogen receptor alpha and Myc transcription factors, and cyclins D1 and E1 as well as cyclin-dependent kinases Cdk1, 4 and 6 as effector molecules. The input was epidermal growth factor (EGF), and the phosphorylation state of the retinoblatoma (Rb) protein was measured in response to siRNA treatments. She systematically perturbed the network components alone and in combinations to identify critical components in the regulation of that network. Indeed, she found novel edges in that network, most of which indicated feedback regulations, for example from cyclin D1 to AKT1 and MEK1. There was a common feeling that such screens will unravel the molecular mechanisms of cellular processes and potentially define major targets for interventions to cure human diseases. But it also became clear that such experiments take months rather than days, which needs to be improved.

The complementation of functional gene-interaction experiments with information on physical protein-protein interactions is a logical next step in the generation of protein networks. Using tandem affinity purification (TAP), Anne-Claude Gavin (EMBL, Heidelberg, Germany) and her collaborators have found that at least 80% of the proteins in yeast exert their function in complexes with other proteins. She stressed the point that protein complexes are, in general, highly dynamic structures, and often the same proteins are components of several protein complexes. To fully understand the modularity of the proteome in all its dynamics and stoichiometry will thus be a true challenge for the coming years.

Two array-based platforms were discussed as tools for qualitative and quantitative proteomics. The nucleic acid programmable protein array (NAPPA) presented by Joshua LaBaer (Harvard Institute of Proteomics, Boston, USA) enables the *in situ* production of large numbers of different protein probes with a success rate of greater than 90%. For use in this system, comprehensive collections of expression plasmids harboring the protein-coding regions of genes are being established at Harvard (in the Flexgene project) and by an international project (the ORFeome Collaboration). LaBaer described how NAPPA arrays have been used to generate protein-protein interaction maps, to test for serum-responsive proteins in the *Pseudomonas* proteome, and to detect tumor-associated antigens as a way of monitoring responses to cancer therapy. On the quantitative side, protein microarrays consisting of spotted protein lysates or antibodies tagged with Odyssey IRDye 680 or IRDye 800 were introduced by Ulrike Korf (DKFZ, Heidelberg, Germany). Detection of signals in the near infrared led to low background, low variability between samples and a high dynamic range. The highly parallel setup of these arrays enabled the dynamics of activation of the kinase ERK after stimulation with erythropoietin to be quantified in cell lines, for example. A problem in applying this method on the genome scale is the availability of high-quality antibodies that must be highly specific for their respective targets.

# Challenges for computational biology and data integration

Ways of automating the analysis of complex phenotypes such as cellular morphology will be needed to speed up the type of screens described above. Advanced methods of image and data analysis for evaluating cellular morphology were described by Wolfgang Huber (European Bioinformatics Institute (EBI), Cambridge, UK), who showed that supervised learning approaches are able to quantify the occurrence of a number of cellular morphological phenotypes in an unbiased manner. Known complex cellular phenotypes are first user defined in a limited number of 'teaching images'. Automated analysis algorithms then recognize these phenotypes and quantify their occurrence in automatically acquired microscope images. Using this approach, Huber and his collaborators have established a cell-morphological phenoprint of the human genome by siRNA-based screens assayed by high-content microscopy.

In regard to data integration, Henning Hermjakob (EBI, Cambridge, UK), who has been involved in developing Human Protein Organization standards for reporting and data collection, stressed the necessity of common standards as prerequisites for efficient data exchange. Given the rapidly increasing number of huge and diverse datasets being generated in the 'multi-omics' sciences, the proper analysis and, even more, the integration of data depends on annotation with enough information to enable researchers to evaluate and understand how the data have been collected and for what purposes they can be sensibly exploited. Reporting guidelines and data-exchange formats from many research communities are in existence, for example, MIAME, MIAPE, and MIACA for microarray, proteomics and cellular assay data, respectively. Hermjakob noted that, unfortunately, many of these guidelines are not yet in general use by the scientific community. Harmonization of the different guidelines to enable the integration of multi-omics data, a prerequisite for systems biology, also remains a challenge.

With human genome sequencing now entering the era of '1,000 genomes' and our personal genomes coming within reach, Rolf Apweiler (EBI, Cambridge, UK) reported on the ongoing implementation of the Human Proteome Project as a natural next step. This project aims to catalog the parts list of all proteins, splice variants, and modifications. Apweiler stressed the need for appropriate technologies, cooperation, data sharing and integration in order to tackle the individual proteomes of cells, tissues, and organisms during growth and development. Compared to the 'mere' 3 billion bases of the human genome, a definitive catalog of the expression pattern of each and every protein in a human being appears to be a Herculean task.

# Taking it into the clinic

The clinical session focused on the impact of genomics on two major human disease areas, cardiomyopathies and cancer. Norbert Frey (University of Heidelberg, Germany) described examples of candidate gene approaches for dilated cardiomyopathy, starting from an *in silico* identification of potential effectors, and leading via ORFeome resources to *in vitro* and *in vivo* validation in zebrafish and mouse models. Frey and his colleagues have identified one gene that is specifically expressed in the heart and localizes to the Z-discs of sarcomeres. When this gene was knocked-down in zebrafish, severe cardiomyopathic phenotypes were seen. This and other genes identified in this study are currently being screened for mutations in patients with cardiomyopathy with the aim of improving diagnosis.

Alexander Marmé (University of Tübingen, Germany) raised the question of what impact genomics had already had on the prognosis and treatment of cancer patients. In breast cancer, the age of the patient, tumor grading, and the receptor status (estrogen receptor, progesterone receptor or ErbB2) are currently utilized to decide on a therapeutic regime. But a decision based on so few biological markers is often of little benefit. A number of gene signatures for breast cancer have already been approved (for example, Oncotype DX (Genomic Health) and MammaPrint (Agendia)) or are in clinical testing (for example, H3E-MC-S080). They are based on sets of molecular and non-molecular predictive factors and should permit tailored therapies, according to Marmé. They should be better suited to a fine-grained stratification of patients, allowing personalized therapies and decreasing the likelihood of overtreating or wrongly treating patients.

A complex interplay between tumor and stromal cells was highlighted by Daniel Mertens (University Hospital, Ulm, Germany). He and his collaborators found that chronic lymphatic leukemia cells quickly die in culture unless they are co-cultured with nurse-like stroma cells. Testing which factors convey the survival message to the tumor cells, they found IL-4 and CD40 to be most effective. The finding was then validated in samples from patients. This stresses the importance of paracrine signals for the growth and survival of tumor cells, and emphasizes the need to study cancer cells within their complex environment.

As the meeting showed, one major challenge is the need for cooperation between different disciplines to push forward and exploit the 'omics' sciences. "We are all looking at the same elephant, just from different angles", says Yarden. "It could turn out in the end though that it had been an octopus all the time", adds Sorger. Acquiring knowledge at the systems level raises the hope that a more comprehensive understanding of cells and tissues in health and disease will open up new avenues for the treatment of patients.

### Acknowledgements

This meeting report is dedicated to Annemarie Poustka, a pioneer in genomics and genome biology and one of the organizers of Systems Genomics 2008, who died on 3 May, 2008.


abstract: Postural tachycardia syndrome (POTS), characterized by orthostatic tachycardia in the absence of orthostatic hypotension, has been the focus of increasing clinical interest over the last 15 years 1. Patients with POTS complain of symptoms of tachycardia, exercise intolerance, lightheadedness, extreme fatigue, headache and mental clouding. Patients with POTS demonstrate a heart rate increase of ≥30 bpm with prolonged standing (5-30 minutes), often have high levels of upright plasma norepinephrine (reflecting sympathetic nervous system activation), and many patients have a low blood volume. POTS can be associated with a high degree of functional disability. Therapies aimed at correcting the hypovolemia and the autonomic imbalance may help relieve the severity of the symptoms. This review outlines the present understanding of the pathophysiology, diagnosis, and management of POTS.
author: Satish R RajAddress for correspondence: Satish R Raj MD MSCI, AA3228 Medical Center North, Vanderbilt University, 1161 21st Avenue South Nashville, TN, 37232-2195, USA. E-mail: <firstname.lastname@example.com>
date: 2006
references:
title: The Postural Tachycardia Syndrome (POTS): Pathophysiology, Diagnosis & Management

# Introduction

Postural tachycardia syndrome (POTS), characterized by orthostatic tachycardia in the absence of orthostatic hypotension, has been the focus of increasing clinical interest over the last 15 years \[1\]. Patients with POTS complain of symptoms of tachycardia, exercise intolerance, lightheadedness, extreme fatigue, headache and mental clouding. This disorder is not new \[2\], but has gone by many different names over the last 150 years, including mitral valve prolapse syndrome, neurocirculatory asthenia, orthostatic tachycardia, and orthostatic intolerance \[3,4\]. An advantage of the name postural tachycardia syndrome (POTS) is that it focuses attention on the sympathetic activation which characterizes the disorder. This review outlines the present understanding of the pathophysiology, diagnosis, and management of POTS.

# Physiology of Upright Posture

Assumption of the upright posture requires prompt physiological adaptation to gravity. There is an instantaneous descent of \~500 ml of blood from the thorax to the lower abdomen, buttocks, and legs. In addition, there is a 10-25% shift of plasma volume out of the vasculature and into the interstitial tissue \[5\]. This shift decreases venous return to the heart, resulting in a transient decline in both arterial pressure and cardiac filling. This has the effect of reducing the pressure on the baroreceptors, triggering a compensatory sympathetic activation that results in an increase in heart rate and systemic vasoconstriction (countering the initial decline in blood pressure). Hence, assumption of upright posture results in a 10-20 beat per minute increase in heart rate, a negligible change in systolic blood pressure, and a \~5 mmHg increase in diastolic blood pressure.

# Pathophysiology of Orthostatic Dysregulation

Failure of the regulatory mechanism to respond properly may lead to either ***orthostatic hypotension***, as is seen in autonomic failure, or ***orthostatic tachycardia***, as is seen in POTS. Orthostatic hypotension is defined as a fall in pressure on standing of more than 20/10 mmHg. However, it is common in patients with autonomic failure for the decline to be much greater than this, which may result in loss of consciousness soon after standing. On the other hand, in POTS, blood pressure is typically maintained on standing or may even increase. Heart rate rises more than 30 bpm and symptoms reminiscent of impaired cerebral perfusion may develop.

# Clinical Presentation of Postural Tachycardia Syndrome (POTS)

## Diagnostic Criteria & Common Clinical Features

POTS is defined (Table 1) as the presence of symptoms of orthostatic intolerance for at least 6 months accompanied by a heart rate increase of at least 30 beats/min within 5-30 minutes of assuming an upright posture. This should occur in the absence of orthostatic hypotension (a fall in blood pressure \>20/10 mmHg). The syndrome must occur in the absence of prolonged bed rest, medications that impair autonomic regulation (such as vasodilators, diuretics, antidepressants or anxiolytic agents), or any other chronic debilitating disorders that might cause tachycardia (such as dehydration, anemia or hyperthyroidism). It is important to recognize that this syndrome is typically disabling. Hence, the mere observation of orthostatic tachycardia is not, by itself, sufficient to make the diagnosis of POTS.

Symptoms include mental clouding ("brain fog"), blurred or tunneled vision, shortness of breath, palpitation, tremulousness, chest discomfort, headache, lightheadedness and nausea. While pre-syncope is common in these patients, only a minority (\~30%) actually pass out. The chest pains are almost never due to coronary artery obstruction, but are sometimes associated with electrocardiographic changes in the inferior leads, particularly when upright \[6\].

Many patients complain of significant exercise intolerance and extreme fatigue. Even activities of daily living, such as bathing or housework, may greatly exacerbate symptoms with resultant fatigue. This can pose significant limitations on their functional capacity.

The disorder primarily affects women of child-bearing age. The female:male ratio is 4:1. The reason for the strong female predominance is not known, but it should be noted that orthostatic tolerance is reduced in normal healthy females \[7\]. Others disorders such as autoimmune diseases and irritable bowel syndrome are seen commonly in patients with POTS, and also have higher prevalence in women.

Patients frequently report that their symptoms began following acute stressors such as pregnancy, major surgery, or a presumed viral illness, but in others cases, symptoms develop more insidiously. About 80% of female patients report an exacerbation of symptoms in the pre-menstrual phase of their ovulatory cycle (unpublished data). Gazit et al. have also reported an association between joint hypermobility and POTS \[8\]. Many patients have bowel irregularities and have been co-diagnosed with irritable bowel syndrome, and some have abnormalities of sudomotor regulation \[9\].

## Psychological Profile in POTS

Patients with POTS are sometimes clinically diagnosed as having anxiety disorders such as panic disorder. Indeed, patients demonstrate elevated scores on the Beck Anxiety Inventory \[10\] (23±10 vs. 7±8; P\<0.001), a commonly used instrument that quantifies the magnitude of anxiety symptoms \[11\]. Unfortunately, this questionnaire includes somatic anxiety symptoms (such as palpitation) which can result from a hyperadrenergic state such as is seen in POTS. When a newer, cognitive-based measure of anxiety (the Anxiety Sensitivity Index \[12\]) is used, there was a trend toward less anxiety in the patients with POTS than the general population (15±10 vs. 19±9; P=0.063) \[11\]. Thus, much of the anxiety attributed to patients with POTS might be due to a misinterpretation of their physical symptoms.

We did find that patients with POTS often have diminished attention and concentration compared to matched healthy volunteers \[11\]. Using the Inattention score from the Connors Adult ADHD Rating Scale \[13\], the patients with POTS scored significantly higher than did the normal control subjects.

## Physical Findings in POTS

The most striking physical feature of POTS is the severe tachycardia that develops on standing from a supine position. Blood pressure and heart rate must be measured in both postures and should be taken not only immediately after standing but also at 2, 5 and 10 minutes as occasional patients have a delayed tachycardia \[14\]. Normal subjects commonly develop a transient tachycardia within the 1st minute of standing that should not be mistaken for POTS. A sustained heart rate increase ≥30 beats per minute is considered diagnostic of orthostatic tachycardia (Figure 1). The systolic blood pressure should not fall by more than 20 mmHg, and in many cases it will actually increase with standing. Recent data suggests that there may be a significant circadian variability in the orthostatic tachycardia seen in patients with POTS \[15\]. In a cohort of 17 patients with POTS, the orthostatic tachycardia was greater in the morning than in the evening (38±4 bpm vs. 27±3 bpm; P\<0.001), while there was no diurnal difference in the orthostatic change in blood pressure. These data suggest that to optimize diagnostic sensitivity, postural vital signs should be performed in the morning.

Cardiac auscultation may reveal a murmur of mitral valve prolapse, but significant mitral regurgitation is unusual. A striking physical feature of POTS is the dependant acrocyanosis that occurs in 40-50% of patients with POTS (Figure 2). These patients experience a dark red-blue discoloration of their legs, which are cold to the touch. This can extend from the feet to above the level of the knees. The reasons underlying this phenomenon are not clear. The current data suggest that the problem is not due to increased pooling in the venous capacitance vessels, but rather due to decreased blood flow in the skin \[16,17\].

## Laboratory Abnormalities in POTS

Some authors advocate the use head-up tilt table testing as a standardized method to assess an individual's response to a change in posture \[1\]. The patient is positioned on a standard tilt table and following baseline measurements of blood pressure and heart rate, the patient is inclined to a 70-degree head-up angle. Blood pressure and heart rate are then measured either continuously or at least every 12 minutes. The orthostatic tachycardia is often measured in a similar fashion to the standing test, with a similar threshold used to diagnose orthostatic tachycardia (an increase of ≥30 bpm) \[1\]. However, the physiology in response to passive standing on a tilt table (with the legs still) is not the same as"active standing" where the patient must support their own weight and maintain their balance. The latter requires use of the "skeletal muscle pump" and mimics real life, while the tilt table does not. For this reason Streeten et al. use similar criteria for orthostatic tachycardia (\>27 bpm), but only with active standing \[18\]. In a recent study, we compared the orthostatic heart rate response of these 2 methods, and found that the tilt table test was associated with an increased orthostatic tachycardia in both patients with POTS and control subjects \[19\]. While both tests were sensitive for the diagnosis of POTS with a 30 bpm threshold for orthostatic tachycardia, the stand test had a specificity of 79% compared to only 23% for the tilt table test.

POTS patients should have only sinus tachycardia. An electrocardiogram should be done routinely to rule out the presence of an accessory bypass tract or any abnormalities of cardiac conduction. A Holter monitor might prove useful to exclude a re-entrant dysrhythmia, especially if the patient gives a history of paroxysmal tachycardia with a sudden onset and sudden offset. Other tests such as echocardiograms are only required in individual cases when there is doubt about the structural integrity of the heart.

We often measure plasma norepinephrine levels in both a supine and standing position (at least 15 minutes in each position prior to blood sampling). The supine norepinephrine is often high normal in patients with POTS, while the upright norepinephrine is usually elevated (\>600 pg/ml), a reflection of the exaggerated neural sympathetic tone that is present in these patients while upright.

Tests of autonomic nervous system function typically show intact or exaggerated autonomic reflex responses. These patients often have preserved vagal function as reflected by their sinus arrhythmia ratio in response to deep breathing. They often have a vigorous pressor response to the Valsalva maneuver, with an exaggerated blood pressure recovery and overshoot both before and after release \[20\].

The blood volume is low in many patients with POTS \[5\]. This can be objectively assessed with nuclear medicine tests to directly measure either the plasma volume or the red cell volume. This knowledge may help to focus the treatment plan.

Some patients with POTS have co-existent complaints of episodic flushing. In about half of these cases there is an associated mast cell activation disorder \[20\]. This can be diagnosed by collecting urine from individual 2-4 hour voids following a severe flushing spell for determination of methylhistamines.

# Differential Diagnosis

The clinical picture of POTS can be confused with pheochromocytoma because of the paroxysms of hyperadrenergic symptoms. Patients with pheochromocytoma are more likely to have symptoms while lying down than POTS patients, and often have much higher plasma norepinephrine levels. The diagnosis of pheochromocytoma is made by assessment of plasma or urinary metanephrines \[21\].

There is commonly some confusion between neurally mediated syncope and POTS. There is a clinical overlap between the 2 disorders, such that about 30% of patients with POTS also have neurally mediated syncope. Nonetheless, most patients with POTS do not faint.

Almost all patients with POTS also have associated fatigue. The reasons are not entirely clear. In some patients, but not all, the fatigue improves with pharmacological control of the orthostatic tachycardia. Some patients with POTS have symptomatic overlap with chronic fatigue syndrome.

# Pathophysiology of POTS

Tachycardia and asthenia on standing is a final common pathway of many pathophysiological processes. POTS is therefore best viewed as a syndrome rather than a disease. Many disorders with a common key clinical presentation (the orthostatic tachycardia) have been described. Over the last decade, much has been learned about specific forms or sub-types within POTS, although a simple test to categorize the individual patient remains elusive. We discuss here the common POTS phenotypes including neuropathic POTS and central hyperadrenergic POTS (Figure 3).

## Neuropathic POTS

Considering that POTS patients have high plasma NE levels, it would seem paradoxical that a neuropathy is proposed as an underlying process. Yet some of them have a form of dysautonomia, with preferential denervation of sympathetic nerves innvervating the lower limbs \[22-24\]. There have been several findings consistent with this hypothesis. The results of sudomotor axon reflex testing \[22\] and galvanic skin stimulation \[23\] support this as well as skin biopsy results \[25\]. Further, these patients have been found to be hypersensitive to infusions of norepinephrine and phenylephrine into veins of the foot, despite high circulating plasma norepinephrine concentrations \[24\]. This suggests that there is a denervation hypersensitivity of the leg veins. Using a segmental norepinephrine spillover approach, Jacob et al. \[26\] demonstrated that patients with POTS had normal sympathetic neuronal norepinephrine release in their arms, but less norepinephrine release (and thus less sympathetic activation) in their lower body.

## Hypovolemia & Blood Volume Regulation

Many patients with POTS have low plasma volumes \[27,28\], but not all. To determine if hypovolemia existed in an unselected group of POTS patients, we studied 15 patients with POTS (not selected for blood volume) and 14 control subjects \[5\]. Plasma volume was measured using ^131^I labeled human serum albumin using a dye dilution technique, and compared to the predicted blood volume for each individual, based upon their height, weight, and gender. As can be seen in Figure 4, the control subjects did not have a significant plasma volume deficit (0.8±2.5%). In contrast, the patients with POTS had a plasma volume deficit of 12.8±2.0% (P\<0.001).

The renin-angiotensin-aldosterone system plays a key role in the neurohormonal regulation of plasma volume in humans. Plasma renin activity and angiotensin II would be expected to increase in response to hypovolemia in order to promote blood volume expansion. Angiotensin II promotes sodium and water retention directly by stimulating sodium resorption in the proximal tubules, and indirectly by stimulating aldosterone secretion.

Patients with orthostatic tachycardia who were also hypovolemic have low levels of standing plasma renin activity and aldosterone compared to normovolemic patients \[21,22\]. This is true in both supine (190±140 pM vs. 380±230 pM; P=0.017) and upright posture (480±290 pM vs. 810±370 pM; P=0.019). One would have expected a compensatory increase in both plasma renin activity and aldosterone given the hypovolemia in these patients. This low level of plasma renin activity and aldosterone is a paradox that remains unexplained. These data suggest that abnormalities in the renin-angiotensin-aldosterone axis might have a role in the pathophysiology of POTS by contributing to hypovolemia and impaired sodium retention. Such hypovolemia could be accounted for by a neuropathic process involving the kidney. A significant modulator of renin release is the sympathetic nervous system. Thus perturbations in the renin-aldosterone system might result from partial sympathetic denervation involving the kidney.

## Central Hyperadrenergic POTS

As a part of the definition, POTS is associated with a hyperadrenergic state (Table 1). In many such cases, the hyperadrenergic state is secondary to a partial dysautonomia or hypovolemia. There are some cases, however, in which the primary underlying problem seems to be excessive sympathetic discharge. These patients often have extremely high levels of upright norepinephrine. While we require the upright norepinephrine level to be \>600 pg/ml for the diagnosis of POTS, the hyperadrenergic subgroup often has upright norepinephrine level \>1000 pg/ml and it is occasionally \>2000 pg/ml. These patients sometimes have large increases in blood pressure on standing, indicating that baroreflex buffering is somehow impaired.

Central hyperadrenergic POTS in its most florid form is much less common than neuropathic POTS, comprising only \~10% of patients. Thus therapy in these cases usually targets a decrease in sympathetic tone both centrally and peripherally.

Central sympatholytics such as methyldopa or clonidine can be used. Peripheral beta-adrenergic blockade may be better tolerated by these patients than by those with neuropathic POTS.

## Norepinephrine Transporter Deficiency

A specific genetic abnormality has been identified in a kindred with hyperadrenergic POTS \[30\]. These individuals have a single point mutation in the norepinephrine transporter (NET). The resultant inability to adequately clear norepinephrine produces a state of excessive sympathetic activation in response to a variety of sympathetic stimuli. While rare, this mutation has taught us much about the importance of a functional NET.

Although functional NET mutations might be infrequent, pharmacological NET inhibition is very common. Many antidepressant and attention deficit medications work at least in part through inhibition of NET. This includes traditional drugs such as tricyclic antidepressants, and newer medications which are pure NET inhibitors (e.g. atomoxetine or reboxetine). Both we \[31\] and others \[32\] have found that pharmacological NET inhibition can recreate an orthostatic tachycardia phenotype in susceptible healthy volunteer subjects. Yohimbine, a central alpha-2 antagonist that will also increase synaptic norepinephrine, can also cause orthostatic tachycardia \[33\].

## Mast Cell Activation

Some patients with POTS have co-existent mast cell activation. These patients have episodic flushing and abnormal increases in urine methylhistamine (the primary urinary metabolite of histamine) \[20\]. Methylhistamine should ideally be measured in 2 hour aliquots at the time of a flushing episode and not just in a random 24 hour period. Other associated symptoms include shortness of breath, headache, lightheadedness, excessive diuresis, and gastrointestinal symptoms such as diarrhea, nausea, and vomiting. Flushing can be triggered by long-term standing, exercise, premenstrual cycle, meals, and sexual intercourse. These patients often have a hyperadrenergic response to posture, with both orthostatic tachycardia and hypertension. They demonstrate a vigorous sympathetic vasopressor response during the Valsalva maneuver with a blood pressure overshoot in late phase II and an exaggerated phase IV blood pressure overshoot. It is not clear if mast cell activation, releasing vasoactive mediators, represents the primary event in these patients or if sympathetic activation, through release of norepinephrine, neuropeptide Y and ATP, is the cause of mast cell activation \[34\].

In these patients, beta-adrenergic antagonists can actually trigger an episode and worsen symptoms. Centrally acting agents to decrease the sympathetic nervous system discharge (e.g. methyldopa or clonidine) may prove effective. Alternatively, treatment could target mast cell mediators with a combination of antihistamines (H1- and H2-antagonists) and with the cautious use of non-steroidal agents (high dose aspirin) in refractory cases.

# Non-Pharmacological Treatment of POTS

No therapy is successful for all patients with POTS. Initial efforts should focus on identifying and treating any reversible causes. Potentially contributory medications (especially vasodilators, diuretics, and drugs that inhibit NET) should be withdrawn. If a patient has been through prolonged bedrest, their symptoms will gradually improve as they recondition themselves to upright posture. Treatment should be optimized for any chronic disease that is present. If there is clear evidence of a re-entrant supraventricular arrhythmia, then this should be treated, including with radiofrequency ablation as appropriate. However, radiofrequency sinus node modification for the sinus tachycardia of POTS is not recommended. This often makes the patient's symptoms worse (and occasionally the patient becomes pacemaker dependent). Specific therapies are summarized in Table 2.

It is important to educate the patient about the nature of the disorder. The patient should avoid aggravating factors such as dehydration, and extreme heat. In order to ensure adequate hydration, we ask our patients to consume 8-10 cups of water daily and to rapidly drink 16 fl oz of water to lower their heart rates \[35\]. In addition, they are asked to aggressively increase their sodium intake up to 200 mEq/day. This is often hard to achieve without NaCl tablets 1 gm/tablet TID with meals. Elastic support hose can help to minimize the degree of peripheral venous pooling and enhance venous return. We recommend 30-40 mmHg of counter-pressure and they should come up to the waist. If the stockings are only knee-high, a line of edema can form just above the stockings. Their use can be limited by their tolerability as the stockings can be hot, itchy and uncomfortable. Exercise (both aerobic and resistance training) is also encouraged and has been shown to be beneficial \[36\]. In addition to reversing any "deconditioning", this intervention can also increase blood volume. Vigorous exercise may acutely worsen symptoms and may even result in prolonged fatigue. It is important that patients start slowly and remain within range of their "target heart rate" in the early stages to avoid symptoms that might discourage further exercise.

Acute blood volume expansion is effective at controlling the heart rate and acutely improving symptoms. Jacob et al. \[37\] found that 1 liter of physiological saline infused intravenously over 1 hour decreased the orthostatic tachycardia from 33±5 bpm before the infusion to 15±3 bpm immediately following the infusion. The physiological saline was more effective at heart rate control than were treatments with either an alpha-1 agonist or an alpha-2 agonist. This treatment is not practical on a day to day basis as a medical setting is required to insert the intravenous catheter and infuse the saline. Recently, there have been reports of patients having regular saline infusions, typically 1 liter of normal saline every other day or every day. Many report an improvement in symptoms. However, there are not yet objective data to substantiate such benefit. Further, there is a risk of vascular access complications or infection. At this time, such therapy for patients with POTS should be considered cautiously.

# Pharmacological Treatment of POTS

No medicines are approved by the United States Food and Drug Administration for the treatment of POTS. Thus all agents are used for this disorder are "off label". Furthermore, there are no pharmacological agents that have been tested in a long-term properly powered randomized clinical trial.

In patients in whom the presence of hypovolemia is either known or strongly suspected, fludrocortisone (an aldosterone analogue) is often used. Through enhanced sodium retention, it should expand the plasma volume, although there is a paucity of data regarding the exact mechanisms of action. Although fairly well tolerated, side effects can include hypokalemia, hypomagnesemia, worsening headaches, acne, and fluid retention with edema. Another volume expanding agent that may be helpful for short-term use is oral vasopressin (DDAVP). This agent causes the kidney to retain free water, but not sodium. Potential side effects include hyponatremia, edema and headache. Erythropoietin has occasionally proven useful in patients with POTS who are refractory to other forms of therapy. While the primary mode of action is likely an increase in intravascular volume via its increase in red cell mass, erythropoietin also appears to have a direct vasoconstrictive effect, possibly through enhanced red cell mediated nitric oxide scavenging \[38\]. Treatment with erythropoietin has many drawbacks including the significant expense and the need for subcutaneous administration.

Central sympatholytic medications are often useful and well tolerated in patients with the central hyperadrenergic form of POTS, but may not be as well tolerated in neuropathic POTS. Clonidine is an alpha 2 agonist that acts centrally to decrease sympathetic nervous system tone. Clonidine, at doses of 0.05 mg to 0.2 mg PO BID, can stabilize heart rate and blood pressure in patients with a large amount of postganglionic sympathetic involvement. Unfortunately, it can also cause drowsiness, fatigue and worsen the mental clouding of some patients. Methyldopa, a false neurotransmitter, is sometimes more successful in controlling symptoms in these patients at doses of 125 mg to 250 mg PO TID \[39\].

When used in low doses, beta-adrenergic antagonists can be useful. We typical use propranolol 10-20 mg PO BID-QID. While this dose range is small, such doses can often have a significant impact on heart rate control, and higher doses are often not tolerated due to hypotension and fatigue.

Since a failure of vascular resistance may be an integral part of neuropathic POTS, vasoconstrictors such as midodrine (an alpha-1 agonist) can be employed \[40\]. Some patients cannot tolerate this agent due to the unpleasant sensation of scalp tingling or goosebumps. Midodrine can also cause hypertension.

We recently reported that an unselected group of patients seen in our inpatient research unit were given a trial of the acetylcholinesterase inhibitor pyridostigmine. By increasing the levels of synaptic acetylcholine at both the autonomic ganglia and the peripheral muscarinic parasympathetic receptors, pyridostigmine significantly restrained the heart rate in response to standing in our patients with POTS. We prescribe pyridostigmine 30mg to 60 mg PO TID alone or in combination with low dose propranolol. Pyridostigmine can enhance bowel motility, so it is not always well tolerated in patients with diarrhea-predominant irritable bowel syndrome symptoms.

While most of the treatments discussed above have focused on the control of heart rate, many patients are also greatly troubled by mental clouding. Modafinil, a stimulant whose mechanism is not yet clear, has been used in some patients with resulting improvement in alertness. However, caution is advised as it may aggravate the orthostatic tachycardia \[41\].

# Conclusions

POTS is a disorder of the autonomic nervous system in which many symptoms can be treated. The cardinal manifestation is symptomatic orthostatic tachycardia. The disorder can produce substantial disability among otherwise healthy people. Patients with POTS demonstrate a heart rate increase of ≥30 bpm with prolonged standing (5-30 minutes), often have high levels of upright plasma norepinephrine, and many patients have a low blood volume. Therapies aimed at correcting the hypovolemia and the autonomic imbalance may help relieve the severity of the symptoms. Continued research is vital to better understand this disorder and to differentiate its various subtypes.

***Funding:*** Supported in part by National Institute of Health grants 2P01 HL56693, K23 RR020783 and M01 RR00095

Criteria for the Postural Tachycardia Syndrome

![](ipej060084-05)

Treatments for the Postural Tachycardia Syndrome

![](ipej060084-06a)

![](ipej060084-06b)

NaCl - Table salt; PO - by mouth; OD - once daily; BID - twice daily; TID - three times daily; QID - four times daily; IV - intravenous


abstract: Interpretation of clinical trials to alter the decline in β-cell function after diagnosis of type 1 diabetes depends on a robust understanding of the natural history of disease. Combining data from the Type 1 Diabetes TrialNet studies, we describe the natural history of β-cell function from shortly after diagnosis through 2 years post study randomization, assess the degree of variability between patients, and investigate factors that may be related to C-peptide preservation or loss. We found that 93% of individuals have detectable C-peptide 2 years from diagnosis. In 11% of subjects, there was no significant fall from baseline by 2 years. There was a biphasic decline in C-peptide; the C-peptide slope was −0.0245 pmol/mL/month (95% CI −0.0271 to −0.0215) through the first 12 months and −0.0079 (−0.0113 to −0.0050) from 12 to 24 months (*P* \< 0.001). This pattern of fall in C-peptide over time has implications for understanding trial results in which effects of therapy are most pronounced early and raises the possibility that there are time-dependent differences in pathophysiology. The robust data on the C-peptide obtained under clinical trial conditions should be used in planning and interpretation of clinical trials.
author: Carla J. Greenbaum; Craig A. Beam; David Boulware; Stephen E. Gitelman; Peter A. Gottlieb; Kevan C. Herold; John M. Lachin; Paula McGee; Jerry P. Palmer; Mark D. Pescovitz; Heidi Krause-Steinrauf; Jay S. Skyler; Jay M. Sosenko; Corresponding author: Carla J. Greenbaum, <firstname.lastname@example.com>.
date: 2012-08
references:
subtitle: : Evidence of at Least Two Distinct Phases From Composite Type 1 Diabetes TrialNet Data
title: Fall in C-Peptide During First 2 Years From Diagnosis

The natural history of type 1 diabetes (T1D) is arguably better understood than that of many other autoimmune diseases, with decades of studies describing the disease course before and after diagnosis. In addition to providing the backdrop for studies to understand the etiopathology of T1D, such information is critical for the design and interpretation of clinical trials to alter the progression of the disease.

The generally understood picture postdiagnosis is of an inevitable fall in β-cell function within a few years after diagnosis, and many studies point to variables that affect the rate of fall, such as glycemic control, HLA type, age at diagnosis, and BMI.

There are several reasons to reexamine the natural history of β-cell function. In recent years, changes in diabetes management and consequent improvement of glycemic control have occurred. In addition, several studies point to a changing HLA distribution in patients with diabetes (1,2), and the overall population generally has had an increase in BMI (3,4). More provocative, there are increasing reports of persistence of C-peptide in individuals long after diagnosis (5) and emerging information from autopsy studies (6) that suggest that the current paradigm should be reconsidered. Furthermore, careful scrutiny of placebo groups from published clinical trials demonstrates major inconsistencies in changes in C-peptide over time between studies, which may be attributable to characteristics of the study populations, procedures used to assess β-cell function, and/or analytic methods used for reporting data.

Type 1 Diabetes TrialNet is an international, multicenter clinical trial network designed to alter the course of T1D, either before diagnosis (prevention) or after clinical diagnosis, with the aim of prolonging β-cell functional survival. As of 2011, TrialNet had acquired data up to 24 months from diagnosis from three clinical trials in individuals with recently diagnosed T1D (7–9). These studies all had similar entry criteria, standardized approaches to diabetes management, and defined protocols for assessment of β-cell function that are highly reproducible (10). In this analysis, we take advantage of this robust dataset to describe the natural history of β-cell function in individuals through 2 years postrandomization, assess the degree of variability between patients, and investigate factors that may be related to C-peptide at and postdiagnosis.

# RESEARCH DESIGN AND METHODS

Data from 191 subjects were included in this analysis, including all subjects from one study in which the intervention had no effect on β-cell function (7) and the placebo-treated subjects from two other studies (8,9). Inclusion of the actively treated subjects from the negative study had no appreciable impact on the results (see below). All subjects or their parents gave written informed consent and assent as appropriate prior to participation in these studies. Pertinent study entry criteria for randomization include peak C-peptide during mixed-meal tolerance test (MMTT) ≥0.2 pmol/mL, positive for at least one diabetes autoantibody, diagnosis of T1D within the previous 100 days, and age 7–45 years. To ensure metabolic stability, no MMTTs were performed before 21 days after diagnosis. The mean (median) time from diagnosis to MMTT was 79 (55) days. The study protocol called for subjects to be contacted by the study team every 2 weeks to evaluate and make recommendations to ensure tight glycemic control. The mean HbA~1c~ at 1 and 2 years was 7.3 (±1.5) and 7.6% (±1.5), respectively.

## MMTT.

As previously described (10), subjects underwent a 2- or 4-h MMTT under the following circumstances: tests were started before 10 a.m., fasting glucose was required to be 70–200 mg/dL, and long-acting insulin was permitted but no short acting insulin (including no pump bolus) was allowed within 2 h before start of test. A standard preparation of fat, carbohydrate, and protein (Boost-HP; Nestle Health Care Nutrition, Inc.) was used at a dose of 6 mg/kg to a maximum of 360 mL.

## Analysis.

Full details of analyses are presented in the [Supplementary Material](http://diabetes.diabetesjournals.org/lookup/suppl/doi:10.2337/db11-1538/-/DC1). Key points are summarized here.

C-peptide values recorded as below "lower limit of detection" (LLD) were assigned the value of one-half the LLD. C-peptide area under the curve (AUC) was calculated using the trapezoidal method. Areas were then divided by the time period of the test, 120 or 240 min as indicated. Undetectable C-peptide on MMTT was defined as all timed values on the MMTT below the LLD.

## Maintenance of C-peptide.

Subjects were classified as having maintained C-peptide over time if there was no change from baseline to each of the time points after baseline. To account for statistical variation in C-peptide measurements, we used three definitions of maintained C-peptide that are suggested by two published studies. All three definitions are similar in that they each consider no change or an increase from baseline to represent a positive response. They differ in the amount of decrease they allow for a subject to still be classified as having maintained C-peptide:

1.  "Percentage Change" definition of maintenance of C-peptide: Subject whose follow-up C-peptide value is no more than 7.5% below baseline. This was defined as "responder" to therapy in work published by Herold et al. (11).

2.  "Inter-test Variability" definition of maintenance of C-peptide: The MMTT/GST (glucagon stimulation test) (10) was a test-retest study comparing C-peptide measurements between the MMTT and the GST. In the MMTT/GST study, individuals underwent two MMTT within a 1-month period. We used the MMTT data from that study to estimate inter-test variability of C-peptide determined by MMTT. In the current analysis, someone whose change from baseline was either nonnegative or if negative, was no more than 1 inter-test SD below baseline, was defined as having maintained C-peptide.

3.  "CV" definition of maintenance of C-peptide: Using MMTT data from the MMTT/GST study, the median coefficient of variation (CV) among the subjects in that study was determined. In the current analysis, the CV for each subject was computed between the baseline and each of the time points (see [Supplementary Material](http://diabetes.diabetesjournals.org/lookup/suppl/doi:10.2337/db11-1538/-/DC1) for details). A subject was then classified as having maintained C-peptide whenever his or her change from baseline was either nonnegative or if negative, represented a CV less than the median CV found in the MMTT/GST study.

We also evaluated the occurrence of an increase in C-peptide that is beyond the amount expected from simple inter-test variability (i.e., an increase of at least 1 inter-test SD from baseline).

Associations between C-peptide measures with baseline covariates were assessed with Spearman correlation for continuous covariates and with ANOVA for categorical covariates. The time course of the proportion of subjects with detectable C-peptide values and the proportion of subjects with peak C-peptide ≥0.2 pmol/mL were estimated with the Kaplan-Meier method.

The relationship of C-peptide across time with baseline covariates was evaluated with mixed linear models and, thus, slopes relating C-peptide and time were estimated for each individual subject. Slopes of C-peptide versus time were estimated for subgroups using the mean slope of individuals in that group and the estimates displayed in fan plots. The joint influence of baseline covariates on the longitudinal change in C-peptide was assessed with multivariable models. Only covariates that were found significant (*P* \< 0.05) in univariable analysis were included in the multivariable models. Piecewise linear regression was used to test the data-driven hypothesis that the slope of C-peptide AUC was the same before and after 1 year postbaseline (12). Slopes unadjusted for covariates were compared between the three end points (fasting, peak, and AUC) using the multivariate analysis described in the [Supplementary Material](http://diabetes.diabetesjournals.org/lookup/suppl/doi:10.2337/db11-1538/-/DC1).

Our study combined data from placebo- and active-treated subjects from the negative Type 1 Diabetes TrialNet MMF/DZB study to increase the number of observations. To evaluate whether inclusion of the actively treated MMF/DZB subjects significantly altered our findings, we replicated the multivariate analyses using a variable to indicate treatment in the MMF/DZB study. This variable was never statistically significant at the *P* \< 0.05 level. In addition, the novel observation of a biphasic fall of C-peptide (described below) was present with or without the actively treated subjects.

# RESULTS

The demographic and baseline characteristics of the 191 subjects included in this analysis are shown in Table 1. Correlations of baseline characteristics with the peak and AUC C-peptide values from their baseline MMTT are also noted in Table 1. Baseline variables that were significantly associated with both peak and AUC C-peptide included age, presence of another autoimmune disease, HbA~1c~, insulin dose (units/kg/day), BMI and BMI *z* score, micro–insulin autoantibody (mIAA) positivity, mIAA titer, and basophils.

Demographic and baseline characteristics and correlations with peak and AUC C-peptide from baseline MMTT

![](2066tbl1)

At entry, all individuals were required to have a peak C-peptide ≥0.2 pmol/mL. Over time, as shown in Fig. 1, only 1% of individuals had undetectable C-peptide at 12 months after study entry and 7% had undetectable C-peptide at 24 months. Post hoc analysis of Diabetes Control and Complications Trial (DCCT) data has suggested that individuals with a peak C-peptide on MMTT ≥0.2 pmol/mL were less likely to have progression of retinopathy and severe hypoglycemia than those with less than that value (13). We therefore evaluated the time until individuals reached this value. As shown in Fig. 1, 88% of individuals continued to have peak C-peptide ≥0.2 pmol/mL at 12 months of follow-up and 66% at 24 months.

We also evaluated changes of three end points from the MMTT (fasting C-peptide, peak C-peptide, and AUC C-peptide) during the 2 years of the study. Comparisons between peak, AUC, and change from baseline using values from the 4- and 2-h tests showed extremely high concordance ([Supplementary Table 1](http://diabetes.diabetesjournals.org/lookup/suppl/doi:10.2337/db11-1538/-/DC1)). Since, by protocol, there were fewer 4-h tests performed, results from the 2-h MMTT were used in subsequent analyses. The slope of the regression of each end point on time, measured in months from the start of the study, was determined. Fasting C-peptide fell at a rate of −0.0076 ± 0.0007, peak C-peptide at −0.0222 ± 0.0010, and AUC C-peptide at −0.0172 ± 0.0007 pmol/mL/month. These slopes were each significantly different from each other (*P* \< 0.001), with fasting C-peptide having the smallest change over time ([Supplementary Table 2](http://diabetes.diabetesjournals.org/lookup/suppl/doi:10.2337/db11-1538/-/DC1)).

Examination of the plots of the mean AUC C-peptide over time suggested a biphasic decline with differences in the slope before and after 12 months (Fig. 2). This difference was not explained by inclusion of individuals who lost C-peptide during the study period because truncating either those subjects or their data points below the LLD did not affect this pattern. We further explored this data-driven hypothesis using piecewise linear regression and found that the decline after 12 months was significantly slower than that seen during the first 12 months and that this was not affected by age. The slope of the AUC C-peptide before 12 months was estimated to be −0.0245 pmol/mL/month (95% CI −0.0271 to −0.0215) as compared with a slope of −0.0079 (−0.0113 to −0.0050) from 12 to 24 months (*P* \< 0.001). In a similar manner, the slope of the peak C-peptide before 12 months was −0.0318 (−0.0357 to −0.0278) as compared with a slope of −0.0089 (−0.0136 to −0.0046) from 12 to 24 months (*P* \< 0.001). The slope of fasting C-peptide before 12 months was −0.03322 (−0.03984 to −0.02659) and after 12 months was −0.00867 (−0.01626 to −0.00108) (*P* \< 0.001).

Inspection of each individual's C-peptide data over time shows the variability in slopes between individuals ([Supplementary Fig. 1](http://diabetes.diabetesjournals.org/lookup/suppl/doi:10.2337/db11-1538/-/DC1)). We then evaluated baseline factors that may contribute to these differences in C-peptide slope ([Supplementary Table 3](http://diabetes.diabetesjournals.org/lookup/suppl/doi:10.2337/db11-1538/-/DC1)). Notable variables not found to be associated with C-peptide over time included Tanner stage and class II HLA type categorized as DR3 or DR4 and not DQB1\*0602 or otherwise. Those variables found to be significantly associated were then evaluated in a multivariable model. As shown in Table 2, only age and number of basophils impacted C-peptide over time whether AUC, peak, or fasting C-peptide was used. Additional baseline variables significantly associated with stimulated measures only (AUC and peak) were BMI *z* score and insulin dose.

Multivariable analysis of baseline characteristics associated with fasting, peak, and AUC C-peptide over time

![](2066tbl2)

We further explored the effect of age on C-peptide over time by grouping individuals according to quartiles according to age, taking the mean slope estimated by the multivariable model of AUC C-peptide. As shown in Fig. 3, the youngest children (aged 7.7–12.3 years) started with lower C-peptide values at their initial MMTT compared with the other subjects. The three older quartiles (aged 12.4–46.1 years) were not different at their initial MMTT. In contrast, the slopes of C-peptide over time showed remarkable concordance in children among the three youngest groups, distinct from that of subjects in the oldest quartile.

Additional exploratory analyses, such as considering the C-peptide in relationship to the simultaneous glucose value, neither improved the model nor changed the impact of previously identified variables on the outcome measure.

We then evaluated time-related patterns of C-peptide preservation, using the classification of subjects as having maintained C-peptide or not, separately for each of the three definitions introduced in research design and methods. As shown in Table 3, large numbers of subjects could be considered as having maintained C-peptide by any definition if all tests are taken into consideration. When limited to comparing the baseline with the 1- or 2-year values alone, 33 (17%) and 21 (11%) maintained C-peptide as defined by the CV definition, respectively, with similar values for the other definitions as described in research design and methods. Multivariable analysis found that age significantly increases, and the presence of islet cell antigen (ICA)512 antibody significantly decreases, the probability of having maintained C-peptide by the CV definition at 2 years (odds ratio age 1.067 \[95% CI 1.026–1.109\]; ICA512 0.329 \[0.162–0.667\]).

Maintenance of C-peptide

![](2066tbl3)

In a similar way, we also investigated time-related patterns of subjects who had strictly an increase in C-peptide of at least 1 inter-test difference SD. There were 55 of 191 subjects who experienced at least one such increase during the 2-year period. In a multivariable model, baseline predictors that enhanced the probability of this increase were increased age, GAD65 antibody positivity, and Tanner stage. Those that decreased the probability of an increase in C-peptide were insulin dose and mIAA and ICA512 positivity and titers.

# DISCUSSION

Loss of insulin secretion is the fundamental defect of T1D, with natural history studies showing a decline before and continuing after clinical diagnosis until a complete absence of endogenous secretion occurs. This natural history serves as the underlying rationale for studies to halt β-cell destruction. Slowing or stopping this loss of insulin secretion prior to diagnosis would delay or prevent clinical onset of disease. Retention of endogenous insulin secretion after diagnosis has been associated with clinical benefits as shown by the DCCT, in which those with preserved function obtained the benefit of intensive therapy (e.g., reduction of retinopathy) with less risk of severe hypoglycemia (14), and in islet transplant studies, in which there is a reduction in hypoglycemia even when insulin independence is not achieved (15).

Our data show that 93% of individuals who started with C-peptide ≥0.2 pmol/mL have detectable C-peptide 2 years from diagnosis, and ∼66% are above the DCCT C-peptide threshold associated with clinical benefit. Furthermore, in contrast to both peak and AUC measures, there is limited change in fasting C-peptide during 2 years from study entry, suggesting that use of nonstimulated C-peptide as an outcome in clinical trials would make it a difficult end point to demonstrate benefit of an intervention therapy.

Most important, our data indicate that the rate of fall is not constant from study entry during the next 2 years. Our data show a biphasic fall during this time; however, with the limited number of fixed time points studied, we cannot exclude the possibility that the true relationship of C-peptide over time is polyphasic. In this regard, it is worthwhile to recall that the baseline MMTT in TrialNet studies is not performed until at least 21 days after diagnosis and that the median time from diagnosis for the initial studies was 55 days; thus, we have no information about the rate of fall from the time of diagnosis to the start of our study. The rate of fall in C-peptide from ∼2 months until 14 months from diagnosis (e.g., 0–12 months from study start) is distinct from the rate of fall from 14 to 26 months after diagnosis (e.g., 12–24 months after study start). This data suggests that there may be metabolic or immunological factors that differ soon after diagnosis rather than later. This hypothesis would need to be explored further. With the caveat that MMTT- and oral glucose tolerance test (OGTT)-stimulated C-peptide are not equivalent (16), it is of interest to note that Diabetes Prevention Trial–Type 1 (DPT-1) data show little change in OGTT-stimulated C-peptide during the 30 months before diagnosis, while a marked fall in peak C-peptide occurred during the peridiagnosis period (17,18). Further insights are likely to come from measuring C-peptide responses under standardized conditions in individuals as they progress from pre- to postdiagnosis. It is also important to note that for these studies, virtually all patients had T1D diagnosed in the community versus the diagnosis of usually asymptomatic T1D from surveillance OGTTs every 6 months in DPT-1 and TrialNet Natural History and Prevention studies (19–21). How the fall in C-peptide would compare after these two very different methods of diagnosis is unknown but of major interest.

It is important to consider these data in the context of results of clinical trials that have preserved β-cell function. In these studies, the differences between the slopes (i.e., rate of fall) of C-peptide between placebo and treatment groups were most pronounced early, with the slopes appearing similar after this initial period (8,9,22,23). The data presented in our analysis raise two hypotheses: *1*) the intervention may only affect the metabolic or immunologic factors soon after diagnosis or *2*) the rate of fall further from diagnosis may be too flat to detect an effect of intervention.

Our data also emphasize the variation in the rate of fall of C-peptide over time and demonstrate that more than one-third of subjects were "nonprogressors" experiencing an increase, no change, or fall within the median CV of the MMTT at least once in the 2 years of study. Approximately 1 in 6 subjects meet this definition at 1 year and \>1 in 10 subjects at 2 years after randomization. As a consequence, one must be cautious about interpretation of small trials or in drawing clinical conclusions from a single phase 2 study.

Similar to previous studies, we found that age, insulin use at baseline, and BMI *z* score at baseline are significantly associated with AUC and peak C-peptide over time in multivariable analysis (24–26). It is notable that variables such as class II HLA type as defined with three categories, Tanner stage, and antibodies (number, positive or not, and titer) that have been reported in previous studies to influence rate of β-cell function decline (27–30) were not significantly associated with AUC or peak C-peptide over time in our multivariable model. Further work to define the role of genotype in disease progression is ongoing, including more detailed analysis of HLA class I and II.

We were particularly interested in age both as a consideration for future study design and to explore the question about whether there are differences in disease progression across the ages studied. The rate of decline of C-peptide was similar in individuals aged 7 to 21 and greater than in subjects older than 21 years. However, the youngest subjects (aged 7 to 12) started with lower C-peptide than older subjects aged 12 to 46 years. This observation is consistent with clinical impressions that younger individuals frequently have low levels of C-peptide but does not support the idea that disease progression is different in younger versus older children or that pubertal status influences the disease process. A major caveat to this conclusion, however, is that the youngest subjects in this study were age 7. Thus, our data do not permit any conclusions about younger children. The different baseline C-peptide level in the youngest group is consistent with the use of an age-dependent percentile determination of intravenous glucose tolerance test data that was used for assessing risk in DPT-1 (31). Unfortunately, little information is available on normal stimulated C-peptide values in young children, a gap that limits our ability to interpret the data in individuals with disease. Our data clearly suggest differences in disease progression between children and adults, pointing to areas ripe for further investigation and also emphasizing that a larger sample size may be required to demonstrate a clinical effect of a drug if only adults are studied. These older patients were diagnosed as T1D by their providers. How their decline in β-cell function would compare with so-called late autoimmune diabetes in adult patients is unknown but also very important for potential intervention trials.

The novel observation of the association of basophils with change in C-peptide over time was unexpected. Indeed, we initially evaluated white blood cell differentials to examine how lymphopenia might relate to clinical course. While historically conceptualized as related to mast cells whose release of interleukin (IL)-4 and IL-13 may affect allergy and protection from parasites, as recently reviewed (32), basophils have multiple roles in the immune response, including antibody production, serving as antigen presenting cells, and amplifying the memory response among others. Since higher basophil levels were associated with a less rapid fall in C-peptide over time, it is tempting to speculate that this association is based on a compensatory response to autoimmunity—attempting to deviate cells via IL-4 cytokine release. However, this association may also have occurred by chance and requires replication in another dataset.

TrialNet studies were conducted at a limited number of clinical centers, with close monitoring of glycemic control, using a standardized approach to MMTT (with regard to meals, insulin dosing, baseline glucose value, and time of day), and centralized laboratories with quality assurance programs. As such, combined data from these studies provide a contemporaneous description of the natural history of C-peptide under clinical trial conditions during the first 2 years after randomization in a context by which effects of intervention can be considered and future studies designed. Since hyperglycemia itself has been associated with poor β-cell function (14), the rate of fall seen in these studies in which individuals had a mean HbA~1c~ of 6.5% on entry and 7.6% at 2 years may not reflect the natural history of disease under usual clinical care. In addition, many of the observations reported must be considered hypothesis generating and require confirmation in additional datasets. To this end, TrialNet will soon use data from two additional studies: one using GAD65-alum (33) and the other involving canakinumb to test the associations observed in the trials used for the current analyses. These studies are being conducted under identical circumstances with the notable exception that subjects as young as age 3 are included in the GAD65 study, thus providing comparative data in this important age-group.

# Supplementary Material

###### Supplementary Data

## ACKNOWLEDGMENTS

The sponsor of the trial was the Type 1 Diabetes TrialNet Study Group. Type 1 Diabetes TrialNet Study Group is a clinical trials network funded by the National Institutes of Health (NIH) through the National Institute of Diabetes and Digestive and Kidney Diseases, the National Institute of Allergy and Infectious Diseases, and the *Eunice Kennedy Shriver* National Institute of Child Health and Human Development, through Cooperative Agreements U01-DK-061010, U01-DK-061016, U01-DK-061034, U01-DK-061036, U01-DK-061040, U01-DK-061041, U01-DK-061042, U01-DK-061055, U01-DK-061058, U01-DK-084565, U01-DK-085453, U01-DK-085461, U01-DK-085463, U01-DK-085466, U01-DK-085499, U01-DK-085505, U01-DK-085509, and Contract HHSN267200800019C, the National Center for Research Resources, through Clinical Translational Science Awards UL1-RR-024131, UL1-RR-024139, UL1-RR-024153, UL1-RR-024975, UL1-RR-024982, UL1-RR-025744, UL1-RR-025761, UL1-RR-025780, UL1-RR-029890, UL1-RR-031986, and General Clinical Research Center Award M01-RR-00400, the Juvenile Diabetes Research Foundation International (JDRF), and the American Diabetes Association (ADA).

No potential conflicts of interest relevant to this article were reported.

The contents of this article are solely the responsibility of the authors and do not necessarily represent the official views of the NIH, JDRF, or ADA.

All authors are members of the Type 1 Diabetes TrialNet Study Group and, as such, contributed to data used in this article. C.J.G. and C.A.B. wrote the manuscript. D.B., S.E.G., P.A.G., K.C.H., J.M.L., P.M., J.P.P., M.D.P., H.K.-S., J.S.S., and J.M.S. contributed to discussion and reviewed and edited the manuscript. C.J.G. and C.A.B. are the guarantors of this work and, as such, had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

# REFERENCES