abstract: # Background
  .
  Gestational Diabetes Mellitus (GDM) increases risks for type 2 diabetes and weight management is recommended to reduce the risk. Conventional dietary recommendations (energy-restricted, low fat) have limited success in women with previous GDM. The effect of lowering Glycaemic Index (GI) in managing glycaemic variables and body weight in women post-GDM is unknown.
  .
  # Objective
  .
  To evaluate the effects of conventional dietary recommendations administered with and without additional low-GI education, in the management of glucose tolerance and body weight in Asian women with previous GDM.
  .
  # Method
  .
  Seventy seven Asian, non-diabetic women with previous GDM, between 20- 40y were randomised into Conventional healthy dietary recommendation (CHDR) and low GI (LGI) groups. CHDR received conventional dietary recommendations only (energy restricted, low in fat and refined sugars, high-fibre). LGI group received advice on lowering GI in addition. Fasting and 2-h post-load blood glucose after 75 g oral glucose tolerance test (2HPP) were measured at baseline and 6 months after intervention. Anthropometry and dietary intake were assessed at baseline, three and six months after intervention. The study is registered at the Malaysian National Medical Research Register (NMRR) with Research ID: 5183.
  .
  # Results
  .
  After 6 months, significant reductions in body weight, BMI and waist-to-hip ratio were observed only in LGI group (P\<0.05). Mean BMI changes were significantly different between groups (LGI vs. CHDR: -0.6 vs. 0 kg/m^2^, P= 0.03). More subjects achieved weight loss ≥5% in LGI compared to CHDR group (33% vs. 8%, P=0.01). Changes in 2HPP were significantly different between groups (LGI vs. CHDR: median (IQR): -0.2(2.8) vs. +0.8 (2.0) mmol/L, P=0.025). Subjects with baseline fasting insulin≥2 μIU/ml had greater 2HPP reductions in LGI group compared to those in the CHDR group (−1.9±0.42 vs. +1.31±1.4 mmol/L, P\<0.001). After 6 months, LGI group diets showed significantly lower GI (57±5 vs. 64±6, P\<0.001), GL (122±33 vs. 142±35, P=0.04) and higher fibre content (17±4 vs.13±4 g, P\<0.001). Caloric intakes were comparable between groups.
  .
  # Conclusion
  .
  In women post-GDM, lowering GI of healthy diets resulted in significant improvements in glucose tolerance and body weight reduction as compared to conventional low-fat diets with similar energy prescription.
author: Sangeetha Shyam; Fatimah Arshad; Rohana Abdul Ghani; Norasyikin A Wahab; Nik Shanita Safii; Mohd Yusof Barakatun Nisak; Karuthan Chinna; Nor Azmi Kamaruddin
date: 2013
institute: 1School of Post Graduate Studies and Research, International Medical University, Kuala Lumpur, Malaysia; 2Department of Nutrition and Dietetics, International Medical University, Kuala Lumpur, Malaysia; 3Endocrine Unit, Department of Medicine, Faculty of Medicine, Universiti Kebangsaan Malaysia (National University of Malaysia), Kuala Lumpur, Malaysia; 4Dietetics Program, School of Healthcare Sciences, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia; 5Department of Nutrition & Dietetics, Faculty of Medicine & Health Sciences, Universiti Putra Malaysia, Serdang, Malaysia; 6Epidemiology and Biostatistics Unit, Department of Social and Preventive Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
references:
title: Low glycaemic index diets improve glucose tolerance and body weight in women with previous history of gestational diabetes: a six months randomized trial

# Background

History of gestational diabetes mellitus (GDM) is a non-modifiable risk factor for developing type 2 diabetes mellitus (T2DM) \[1,2\]. Frequently, women with prior GDM exhibit tendencies for central obesity, insulin resistance and glucose intolerance \[3\]. Thirty-three to 50% of GDM women develop overt T2DM five years after delivery \[4\]. At ten years postpartum, 35–60% of GDM women are known to develop type 2 DM \[3\]. Hence GDM represents a challenging group to institute effective intervention \[5\].

Intensive lifestyle intervention has shown to be effective in reducing risk for T2DM in high risk individuals \[6,7\]. Conventional diets for primary prevention of T2DM consistently support energy-restricted, low-fat, and high–complex carbohydrate regime to achieve weight loss \[8,9\]. However, such interventions have shown limited success in reducing postpartum weight in women after GDM \[10\].

Meanwhile, emerging evidence emphasizes the role of insulin secretion and insulin resistance in body weight regulation \[11\]. Therefore, dietary factors that influence these parameters would include the type of carbohydrate defined by its glycaemic index (GI) and its overall glycaemic potential described by its glycaemic load (GL, i.e. sum of the product of GI and available carbohydrate amounts for all foods consumed in the diet \[12\]) are known to modulate weight loss, especially in hyper-insulinaemic women \[13,14\]. Low GI diets also improve glycaemic control in Asian diabetics \[15\] and reduce risk for T2DM \[16\]. However the effect of lowering dietary GI in women with prior GDM is currently unknown. This study aimed to evaluate the effect of adding low GI dietary advice to conventional dietary prescription on glycaemic variables and body weight in comparison to conventional dietary prescription among women with previous GDM.

# Methods

This study was conducted at the endocrine clinic of a tertiary hospital. The project was approved by the Ethic and Research Review Committees of the institutions involved, in-line with national regulations and according to the International Harmonization Consensus on Good Clinical Practice. The study is registered at the Malaysian National Medical Research Register with Research ID: 5183. The trial was carried out according to Consolidated Standards of Reporting Trials (CONSORT) guidelines.

## Inclusion and exclusion criteria

Healthy women in the age group of 20–40 years old, with a history of GDM (defined according to WHO criteria, \[17\]), and high risks for developing T2DM were included. While GDM itself is a non-modifiable risk factor for T2DM, certain modifiable risk factors that increase the risk in this group of subjects have been identified. These include central obesity, higher postpartum body mass index (BMI), fasting blood sugar (FBS), 2 h post-load blood glucose (2HPP) and energy intake \[18,19\]. Hence preventive interventions would be especially beneficial to subjects who have high risks as indentified by the inclusion criteria of the study. We therefore defined high risk as satisfying one of the following four conditions: BMI\>23 kg/m^2^, or waist circumference\> 80 cm \[20\], or impaired glucose tolerance (IGT) defined as 2HPP after 75 g screening oral glucose tolerance test (OGTT) ≥7.8 and\<11.1 mmol/L or impaired fasting glucose (IFG) defined as FBS\>5.6 mmol/L or a family history of T2DM. Exclusion criteria were the diagnosis of T2DM (FBS≥7.0 mmol/L, or 2HPP≥11.1 mmol/l, \[17\], or presence of other health complications and usage of drugs affecting body weight and glucose control. Written informed consent was obtained from all participants. The women were enrolled into the trial at a minimum of two months after their last GDM delivery.

## Measurement of outcome variables

The primary end point of this study was 2HPP after a 75 g oral glucose tolerance test was administered. FBS, fasting serum insulin (INS) and anthropometric measures were the secondary endpoints investigated.

Body weight rounded to 0.1 kg was measured in light clothing, after emptying pockets and without footwear, using digital weighing scales (Model: BWB-800A, Tanita Corporation, Tokyo, Japan). Height without footwear was measured using the wall mounted stadiometer (Model No. 206, SECA, Hamburg, Germany), rounded to 0.1 cm to calculate BMI. BMI was calculated as the ratio of weight in kg to the square of height in m^2^. Waist and hip circumference in cm was measured as per WHO guidelines \[21\] and waist-to-hip ratio was calculated. All anthropometric measurements were done by a single researcher to avoid bias. Anthropometric measurements were made at baseline, three and six months after intervention.

Blood samples were collected after a 12-h fasting, and analysed for FBS and insulin. A 75 g OGTT was administered and 2HPP samples were obtained. Blood glucose was analysed using the G6PD/Hexokinase method as per routine medical centre laboratory protocol. Serum samples for INS were frozen at −20°C until batch processed for analysis. INS was analysed with chemiluminescent enzyme-labelled immunometric assay, using Immulite 2000 automated analyser (Diagnostic Products Corporation, Los Angeles, USA). Blood glucose and INS values were measured at baseline and 6 months after intervention.

Dietary intake was assessed with 3-day dietary records. The subjects were asked to report intake for any 2 weekdays and one weekend day for each visit. Subjects were trained to use the diet records at the screening visit and pictures of household measures were provided to assist the subjects with recording the amounts. Diet records were collected at baseline, three and six months after intervention. All food records were reviewed with subjects during their follow up visits by the research nutritionist to ensure completeness of entries.

GL by definition is the "product of the GI of foods and its carbohydrate content" \[22\]. GL for individual food items in the dietary record was calculated as the product of diet GI and carbohydrate intake divided by 100 \[23\]. Dietary GL represents both the quantity and the quality of carbohydrate in diet \[22\] and was calculated as sum total of GL of foods consumed in the day \[24\]. Diet GI was calculated using the formula Diet GI= Diet GL×100/amount of carbohydrate in the diet \[24\].

A Microsoft Excel-based food composition database and diet intake calculator- "DietPLUS Version 3" was built for this study and was used for dietary analysis \[25\]. Due to lack of availability of local GI values, GI values for numerous Malaysian foods needed to be matched or estimated. Hence a systematic GI value assignment to foods in the Malaysian food composition table to similar foods published internationally was undertaken. To improve the accuracy of this GI-matching process, the GI assignment was based on previously published methodology \[26\]. The international GI and GL database and its updated version the online database of University of Sydney was used for this purpose \[27,28\]. The methodology of adding glycaemic index and glycaemic load functionality to the Malaysian food composition database has been previously published \[25\].

International Physical activity short Questionnaire (IPAQ-short) was used to assess physical activity levels of the subjects \[29\].

## Randomisation

All eligible subjects (n=77) were randomized strictly according to a computerized allocation (1:1) list generated using randomisation software \[30\]; by an individual from outside this research group. The researchers were unaware of the sizes of blocks used. Participants were randomized to either a conventional healthy dietary recommendation (CHDR) or the "CHDR+Low GI" group (LGI).

## Dietary intervention

Details on the educational intervention and tools used have been published earlier \[31\]. However for the sake of completeness a brief description is provided here. The aim of the nutrition education was to achieve and maintain a 5-7% reduction in body weight if BMI\>23 and maintain current weight if BMI\<23 during the one year complete trial period. The nutrition intervention aimed to achieve this objective through establishing two diets that were similar in energy and macronutrient content but with different dietary GI. Individual energy requirement was calculated by multiplying basal metabolic rate (BMR) by an appropriate activity factor \[32\] based on reported physical activity pattern and occupation. Harris Benedict method was used to calculate BMR \[32\]. If the subject had a BMI\>23 and if she was not breast feeding, the energy prescription was reduced by 500 Kcal. Subjects with BMI\< 23 or those breastfeeding an infant\<6 mo of age were prescribed their energy requirement (energy prescribed=energy requirement). All EP was rounded to the nearest hundred. Energy prescription was capped at 1800 Kcal/day. Each subject was given an individualized dietary sheet with the recommended number of servings of each food group per day according to their energy prescription. Subjects were taught meal planning based on their individualized energy prescription and a sample one day menu was provided during the intervention visit. Concepts of serving size, number of servings and food exchange groups were taught to both groups of subjects. These dietary prescriptions were indicative in nature as the study subjects were "out-patients" and intervention was educational in nature.

Primary nutrition educational intervention was administered through a structured one-to-one session with the research nutritionist, at baseline. Conceptual guidance to achieve conventional recommended diet (CHDR) low in fat and refined sugars, and high in fibre was provided using the 5M framework proposed by the Malaysian Ministry of Health ( minimize salt, sugar, oil, more fruit and vegetables) \[33\]. Subjects were encouraged to indulge in moderate physical activity for 30min, at least five times a week.

The LGI group in addition to the above conventional recommendations also received a GI-education component that taught subjects to substitute high GI foods with low GI options. Staple foods primarily determine dietary GI \[34\], hence, GI-education focused on the strategies to select low-GI options for high GI rice, bread and breakfast cereals. Subjects were advised to restrict rice intake to once per day since most locally available rice varieties were high in GI \[35\]. They were encouraged to choose lower GI foods like spaghetti, noodles or multi-grain bread at other times. Subjects were not required to memorize numerical GI values of foods. However a list of foods that classified foods as high, moderate or low GI was provided to aid making choices. The LGI subjects were asked to include one low GI food at each meal.

Colour coded (pink for LGI and blue for CHDR) take-home booklets were also provided to the subjects as added reference. To improve retention of participants in the trial two electronic interactions (short messaging service (SMS) or e-mail, as per the subject's preference) per month was established. These contacts were similar between the groups in terms of frequency and content of delivery.

## Sample size calculation

Sample size was calculated to detect at the end of one year, a 1.5 mmol/L difference in the postprandial blood glucose, the primary end point for this study. This difference is thought to be of clinical significance \[36\] between the diet treatments, with a power of 80%. This was based on the assumption that the standard deviation of the response variable is 1.5 mmol/L \[37\]. A total of 34 subjects, 17 per group, were required for this study. Taking into account the higher attrition rates in preventive trials \[38\], and reported reluctance among women post-GDM to participate \[5\], we started with a bigger sample size.

## Statistical analysis

Statistical analyses were performed using IBM SPSS (Version 19, Somers, NY, USA). The effect of the respective dietary interventions on anthropometric measurements and glycaemic variables at the end of 6 months was investigated. Primary analysis included intent to treat analysis of anthropometric data and glycaemic variables. Missing data was imputed conservatively with the last observation carried forward technique. A secondary analysis was carried out using the completers' analysis. For the dietary data analysis the baseline values and a mean of the intake at three and six months visit was used. A sub-analysis to determine the differential response to the dietary intervention in subjects with varying fasting insulin levels was carried out. Fasting insulin value of 2 μIU/ml was chosen to be the cut-off for this analysis since it was approximately the natural median INS value for our subjects

The statistical significance standard was set at 5%. Data normality was tested using the Shapiro–Wilks test. Data is presented as Mean ± SD, unless stated otherwise. Differences between groups were assessed using independent samples *t* test and changes in outcomes before and after intervention were analysed using paired *t* tests. When the test assumptions were not met, Mann–Whitney U-test test for two samples was used to compare values between groups and Wilcoxon Sign test was used to compare the changes in outcome within the group. Effect size values were computed to compare the effects of the diet treatments \[14\]. Effect sizes between 0.2-0.5, 0.5-0.8 and \>0.8 were taken to denote "small", "moderate" and "large" changes in outcomes \[14\].

Linear regression analysis was used to study the role of energy intake, macronutrient intakes, dietary fibre, GI and GL as predictor variables on changes in body weight. In modelling 2HPP, in addition to the above mentioned predictors (dietary variables), change in body weight was included. In modelling FBS, in addition to dietary variables mentioned above, changes in body weight and 2HPP were included. A sub-analysis was done grouping subjects with INS\<2 μIU/L and ≥2 μIU/L in studying the models as attempted above. We also wanted to test if the effect of GI on 2HPP was mediated by changes in weight, among the subjects with INS≥2 μIU/L. In this test the Sobel's Method was used \[39\].

# Results

Seventy-seven subjects were recruited out of whom a total of 62 (29 in CHDR and 33 in LGI group) completed the 6 months on the trial (refer to Figure 1). The two groups had comparable baseline characteristics as shown in Table 1.

Baseline characteristics of subjects (Mean±SD)

| **Characteristic** | **LGI** | **CHDR** | **P**^**1**^ **Value** |
|:---|:--:|:--:|:--:|
| Age (y) | 30.9±4.3 | 31.5±4.5 | 0.999 |
| No. of Pregnancies\* | 2±2 | 2±1 | 0.245 |
| No. of GDM Pregnancies\* | 1±0 | 1±1 | 0.891 |
| Parity\* | 2±2 | 2±2 | 0.671 |
| Duration since Last GDM delivery (mo)\* | 6±3 | 5±2 | 0.246 |
| Weight (kg) | 65.3±11.5 | 64.6±12.5 | 0.794 |
| BMI (kg/m^2^) | 26.4±4.6 | 26.3±4.6 | 0.952 |
| % subjects with BMI\>23 (Overweight) | 74.4 | 71.1 | 0.802 |
| % subjects with BMI\>25 | 59 | 63.2 | 0.816 |
| % subjects with BMI\>27.5 (Obese) | 38.5 | 47.5 | 0.494 |
| % subjects breast feeding | 10.3 | 21.1 | 0.420 |
| Waist Circumference (cm) | 83.2±8.5 | 82.7±9.6 | 0.789 |
| Waist: Hip Ratio | 0.81±0.06 | 0.80±0.05 | 0.608 |
| Fasting blood glucose(mmol/L) | 4.7±0.54 | 4.8±0.53 | 0.405 |
| 2 h post 75 g OGTT blood glucose (mmol/L) | 6.8±1.6 | 6.2±1.4 | 0.067 |

Legend: *LGI* Low GI Group, *CHDR* Conventional healthy Dietary Recommendation Group.

\*Expressed as median±interquartile range, P^1^ Value: test between groups.

## Changes in anthropometry

Intent to treat (ITT) analysis showed significant reductions from baseline to six months in body weight (P=0.018), BMI (P=0.008), waist circumference (P\<0.001) and waist-hip-ratio (P=0.02) in LGI group. In CHDR group there was a significant reduction in waist circumference (P=0.048) only (Refer Table 2). The effect sizes for the changes in weight, BMI, waist circumference and waist-hip-ratio from baseline to six months in the LGI group were 0.40, 0.45, 0.70 and 0.38, respectively which are moderate to large. The effect sizes for the changes in the same variables in the CHDR group were merely 0.02, 0.02, 0.33 and 0.22, respectively.

Anthropometric outcomes during the course of the study (Mean±SD)

| **Outcome** | **LGI** |  |  | **CHDR** |  |  |
|:---|:--:|:--:|:--:|:--:|:--:|:--:|
|  | **baseline** | **3 months** | **6 months** | **baseline** | **3 months** | **6 months** |
| Weight (Kg) | 65.3±11.5^a^ | 64.6±11.5^b^ | 64.0±11.7^ab^ | 64.6±12.5 | 64.7±12.6 | 64.5±13.0 |
| BMI(kg/m2) | 26.4±4.6^a^ | 26.0±4.7^a^ | 25.8±4.7^a^ | 26.3±4.6 | 26.4±4.7 | 26.3±4.8 |
| WC (cm) | 83.2±8.5 ^a^ | 83.0±10.4^b^ | 80.5±9.1^ab^ | 82.7±9.6 ^a^ | 82.5±10.8 | 81.5±10.1^a^ |
| WHR | 0.81±0.06^a^ | 0.80 ±0.06 | 0.79 ±0.05^a^ | 0.80±0.05 | 0.80±0.05 | 0.79±0.05 |

Legend: *LGI* Low GI Group, *CHDR* Conventional healthy Dietary Recommendation Group, *BMI* Body mass index, *WC* waist circumference *WHR* waist hip ratio.

For each group, values in a row with similar alphabetical superscripts show significantly different means in paired tests.

As shown in Figure 2, a greater number of subjects achieved a percentage weight loss≥5% in LGI as compared to CHDR Group (33% vs. 8%, P=0.01)

## Changes in glycaemic variables

The subjects had normoglycaemia or dysglycaemia (impaired fasting glucose/ impaired glucose tolerance) as tested by 75 g OGTT at baseline. FBS and 2HPP levels in the two groups were comparable at baseline (See, Table 3).

Changes from baseline in glycaemic values (Mean±SD)

|   | **LGI** |  |  | **CHDR** |  |  |
|:---|:--:|:--:|:--:|:--:|:--:|:--:|
|   | **Baseline** | **6 months** | **P**^**1**^ | **Baseline** | **6 months** | **P**^**1**^ |
| FBS (mmol/L) | 4.7±0.53 | 5.0±1.2 | 0.060 | 4.8±0.53 | 4.9±0.53 | 0.111 |
| ∆FBS (mmol/L)\* | −0. 2 (0.6) |  |  | 0.1(0.6) |  |  |
| 2HPP (mmol/L) | 6.8±1.6 | 6.8±2.8 | 0.960 | 6.2±1.4 | 6.8±1.6 | 0.010 |
| ∆2HPP (mmol/L)\* | −0.2 (2.8) ^a^ |  |  | 0.8 (2.0)^a^ |  |  |

Legend: *LGI* Low GI Group, *CHDR* Conventional healthy Dietary Recommendation Group. *FBS* Fasting blood sugar, *2HPP* 2 hour post load blood glucose after 75 g OGTT. P1: Significance of changes within groups.

\* Data presented as median (interquartile range).

^a^ Difference between groups significant (P=0.025).

From baseline to 6 months, the changes in fasting blood sugar were not significant in both groups (See, Table 3). There was no significant change in median 2HPP in the LGI group (−0.2 (IQR: 2.8) mmol/L, P= 0.960). In the CHDR group, there was a significant increase in median 2HPP (+0.8 (IQR: 2.0) mmol/L, P=0.01). The changes in 2HPP were significantly different between groups (P=0.025, See, Table 3).

Results obtained from per-protocol analysis for changes in anthropometric and glycaemic outcomes were similar to the respective analysis done using ITT (data for per-protocol analysis not shown here).

## Baseline glucose tolerance status and response to dietary treatment

The anthropometric and glycaemic changes among subjects varying in baseline glucose tolerance status are shown in the following Table 4. There was a slight increase in weight and 2HPP blood glucose among subjects with dysglycaemia in CHDR group but in the LGI group there was a slight decrease in these two measurements. Among subjects with dysglycaemia at baseline 37.5% of subjects in CHDR (n= 3/8) and 64.3% in LGI (n=9/14) reverted to normoglycaemia (RR: 1.5, P= 0.378).

Anthropometric and glycaemic changes in subjects with varying glucose tolerance status during the six months study period (Mean±SD)

| **Baseline glucose tolerance status** | **Normoglycaemia** |  |  | **Dysglycaemic subjects** |  |  |
|:---|:--:|:--:|:--:|:--:|:--:|:--:|
| **Outcome changes** | **CHDR** | **LGI** | **P** | **CHDR** | **LGI** | **P** |
| **Weight (kg)** | −0.2±2.72 | −1.93±3.48\* | 0.446 | 0.5±2.97 | −0.7±3.37 | 0.446 |
| **BMI (kg/m2)** | −0.08±1.04 | −0.76±1.41\* | 0.077 | 0.25±1.2 | −0.6±1.54 | 0.230 |
| **WC (cm)** | −1.33±3.34 | −3.72±4.24\*\* | 0.046 | −2.14±4.53 | −2.67±3.66\* | 0.786 |
| **WHR** | −0.01±0.04 | −0.02±0.005 | 0.427 | −0.02±0.05 | −0.03±0.03\* | 0.282 |
| **FBS (mmol/L)** | 0.15±0.41 | 0.31±0.53\* | 0.290 | 0.04±0.45 | 0.49±1.7 | 0.507 |
| **2HPP (mmol/L)** | 0.88±1.2\*\*\* | 0.24±2.04 | 0.216 | 0.47±2.22 | −0.49±4.05 | 0.572 |

Legend: *LGI* Low GI Group, *CHDR* Conventional healthy Dietary Recommendation Group. *BMI* Body mass index, *WC* waist circumference, *WHR* waist hip ratio, *FBS* Fasting blood sugar, *2HPP* 2 hour post load blood glucose after 75g OGTT.

P values show the significance of difference in changes between groups.

Values with asterisks denote significant changes in paired-tests, \*P≤0.05, \*\*P≤0.01, \*\*\*P≤0.001.

## Fasting insulin levels and response to dietary treatment

Out of the 77 subjects, 44 (57.1%) had INS\<2 μIU/L and 33 (42.9%) had INS≥2 μIU/L. The percentage of subjects with INS\<2 μIU/L in the LGI and CHDR groups were 61.5 and 52.6% respectively. This difference between the groups was not significant (P=0.228).

Among the subjects with INS\<2 μIU/L, there was no significant difference in the anthropometric and glycaemic changes for both LGI and CHDR groups (data not shown).

As shown in Figure 3, among subjects with baseline INS≥2 uIU/ml the percentage weight loss was higher in the LGI group compared to the CHDR group (−3.1% vs. + 0.2%, P=0.09).

For 2HPP, LGI subjects with baseline INS≥2 μIU/ml, recorded a significant reduction (−1.9±0.42 mmol/L, P=0.002) while the 2HPP levels increased (1.31± 1.4, P=0.004) among similar subjects in the CHDR group (See Figure 4). The level of 2HPP changes between the groups was significant (P \<0.001). A sizable increase in 2HPP levels among subjects with baseline INS≥2 μIU/ml, was noted among those in the highest GI quartile (P value for trend =0.019, See Figure 5). There was no significant association between GI and changes in 2HPP among subjects with baseline INS\<2 μIU/ml (P=0.576, See Figure 5).

Changes in FBS were however not significant within or between diet groups in such subjects (data not shown).

## Changes in dietary intake

Food records were collected from the subjects at baseline, at 3 months and at 6 months. Food records from 34 subjects in LGI group and 31 subjects in CHDR group were used in the analysis. The results of the dietary analysis are presented in Table 5. The after intervention values are the average between three and six month values.

Dietary intake of subjects before and after intervention (Mean ± SD)

| **Dietary outcome** | **LGI** |  |  | **CHDR** |  |  | **P values for difference in changes between groups** |
|:---|:--:|:--:|:--:|:--:|:--:|:--:|:--:|
|  | **Baseline** | **After intervention** | **P**^**1**^ | **Baseline** | **After intervention** | **P**^**1**^ |  |
| Calories | 1804±495 | 1660±368 | 0.075 | 1721± 491 | 1612±352 | 0.171 | 0.970 |
| CHO g | 245±75 | 206±52 | 0.002 | 225±68 | 220±48 | 0.627 | 0.224 |
| CHO en% | 55±9 | 51±5\*\* | 0.050 | 53±7 | 55±7\*\* | 0.240 | 0.065 |
| Protein g | 66±21 | 69±15 | 0.323 | 70±26 | 63±21 | 0.119 | 0.191 |
| Protein en% | 15±4 | 20±6 | \<0.001 | 16±5 | 19±7 | 0.124 | 0.400 |
| Fat g | 62±23 | 58±18 | 0.418 | 60±20 | 53±16 | 0.064 | 0.695 |
| fat en% | 29±8 | 28±5 | 0.368 | 30±6 | 25±7 | 0.004 | 0.177 |
| Dietary Fibre (g) | 13±5 | 17±4\*\*\* | 0.001 | 13±5 | 13±4\*\*\* | 0.583 | 0.022 |
| Glycaemic Index | 62±5 | 57±5\*\*\* | 0.003 | 62±7 | 64±6\*\*\* | 0.4 | 0.033 |
| Glycaemic Load | 152±41 | 122±33\* | \<0.001 | 142±42 | 141±35\* | 0.854 | 0.085 |

*LGI* Low GI Group, *CHDR* Conventional Healthy Dietary Recommendation Group.

P^1-^ P values for changes within groups.

\*Values significantly different between groups - (P\<0.05), \*\*Values significantly different between groups (P=\<0.01). \*\*\*Values significantly different between groups (P=\<0.001).

Baseline dietary intakes were comparable between groups. In the LGI group, mean percentage of calories from carbohydrate, amount of carbohydrates, diet GI and GL decreased significantly from baseline, while percentage of energy from protein and dietary fibre increased significantly. The only significant dietary change from baseline in the CHDR group was the reduction in the percentage of energy from fat. After six months, mean percentage of calories from carbohydrate, GI and GL were significantly lower in the LGI compared to the CHDR group. Fibre intake was significantly higher in the LGI group. During the study period, only changes in dietary glycaemic index and dietary fibre intakes were significantly different between groups (Refer Table 5).

Based on the results from regression analysis, mean GL during the six months after intervention was the single independent predictor of weight loss in subjects (R^2^= 13.5%, standardized B= 0.37, P= 0.003). Weight change was the single independent predictor of changes in 2HPP (R^2^= 7.4%, standardized B= 0.272, P= 0.02). Change in 2HPP was the independent predictor of change in FBS (R^2^=32. 7%, standardized B= 0.572 P\< 0.001).

In subjects with INS≥2 μIU/L, mean GI primarily explained changes in 2HPP mean (R^2^=43. 8%, standardized B= −0.662 P\< 0.001), with reduction in 2HPP being caused by a reduction in GI. Further analysis with block regression showed that mean GI explained 43.8% of the change in 2HPP while weight change explained only an additional of 3.9% (P=0.227) in these subjects. The Sobel's method was used to further determine if the effect of GI on 2HPP was mediated through changes in weight. The results showed that mediation effect was small and not significant in subjects with INS≥2 μIU/L (Indirect effect vs. Direct effect: unstandardized B= −0.05 vs. 0.196, P values 0.716 vs. \<0.001).

## Physical activity and adherence

Physical activity levels remained comparable between the groups at baseline (LGI vs. CHDR: median (IQR):608 (2727) vs. 900(2304) MET.min/week, P=0.143) and at the end of six months study period (933 (1403) vs.965 (857) MET.min/week, P= 0.908). Dietary adherence (self reported and calculated, data not shown here) were statistically comparable between the groups.

# Discussion

The current study was designed to investigate the effects of adding low-GI nutrition education to conventional healthy dietary advice in subjects with previous history of GDM. Baseline characteristics were well matched in terms of socio-demographic and metabolic variables. Subjects in the LGI group of this study lost an average of 1.3 kg compared to the 0.1 kg loss in the CHDR arm, after six months on the trial. These findings are in agreement with the Cochrane review which concluded that subjects on low GI diets lost an average of 1 kg more than subjects on high GI diets, in trials that lasted up to 6 months in duration \[40\]. In this study, more post-GDM subjects in LGI group achieved a moderate 5% weight loss (P=0.01). Hence, low GI diets aid weight loss in the study population of women with previous GDM as compared to conventional healthy diets with similar energy prescriptions, during a 6 month period.

Moderate weight loss in the range of 5-10% has been proven to improve cardio-metabolic risk in high risk subjects \[41\]. Furthermore, every 1 kg weight reduction achieved in the first year of the Diabetes Prevention Program (DPP) translated into a 16% reduction in risk for conversion to T2DM \[42\]. Hence by promoting moderate weight loss in the group of post-GDM subjects, LGI diets may contribute effectively to lowering their cardio-metabolic risks.

CHDR subjects had a significant increase of 0.6 mmol/L from the baseline 2HPP levels, after six months' intervention. The magnitude of this change described by its effect size is "moderate" and remains a cause for concern in GDM women who are known to be at an increased risk for development of glucose intolerance \[3\]. Therefore, conventional healthy diets that emphasize on calorie and fat control do not benefit these women with prior GDM, in terms of improving glucose tolerance.

The LGI group, on the contrary, had maintained their 2HPP levels during the same period of study. As an increase in 2HPP predominantly represents glucose intolerance \[17\], lowering of 2HPP within these subjects by LGI diet would lead to the reduction of the prevalence of abnormal glucose tolerance. This line of thought finds further support in the higher rate of reversal to normoglycaemia observed among IGT subjects in LGI group after six months (50% vs. 40%, P= 0.689.). Furthermore, post-challenge plasma glucose spikes are thought to be more strongly associated with risk for atherosclerosis than FBS in a cohort at risk for diabetes \[43\]. Hence, the improvement in glucose tolerance could delay or prevent the subsequent development of T2DM and its complications in this high risk group of subjects.

There is a paucity of data on the normal fasting insulin range for young healthy Malaysian women. A Malaysian study among 30 healthy volunteers reported a median fasting insulin level of 4.7 μIU/ml with a central 95% range of 2.1 to 12.1 μIU/ml \[44\]. Baseline INS in 18/38 subjects in CHDR group and 15/39 subjects in LGI group were \<2 μIU/ml. Given that women with prior GDM have innate tendencies towards insulin resistance \[45\], one would expect our study population to have higher fasting insulin levels. It was unexpected that 57% of our subjects would have INS less than the 2.1 μIU/ml. However, Farhan et al., (2012) also found the mean fasting insulin values, of a small group (n=10) of Austrian GDM women, at 3 month postpartum to be 1.63 μIU/ml. One possible explanation for this occurrence is that only 43% of our subjects could be classified as being obese (BMI\>27.5) \[46\], which could have resulted in the normoglycaemic state represented in the fasting blood glucose and normal or low INS. The median BMI of this study group was 26, and hence these subjects could be defined only as being mildly overweight based on the WHO criteria \[47\]. This finding suggests that despite their inherent insulin resistance accentuated by pregnancy, these subjects were at a very early stage of pre-diabetes, making early detection and intervention necessary if not paramount. We acknowledge that a large cross sectional study of healthy Malaysian individuals is necessary to determine normal reference fasting insulin range for this population.

The dietary intervention resulted in significant different outcomes in subjects with baseline INS≥2 μIU/ml with respect to anthropometry and 2HPP. For subjects with baseline INS≥2 μIU/ml the greatest improvement in glucose tolerance was noted among subjects in the lowest quartile for dietary GI at 6 months. Furthermore these subjects also achieved more weight loss when on LGI diets. These findings are consistent with the 6 months finding from the CALERIE study which reported that women with higher postprandial insulinaemic response lost more weight on low GI diets after 6 months on intervention \[14\]. However the mean baseline fasting insulin levels in the CALERIE subjects was 11.9 μIU/ml, which was much higher than the mean for this study group.

Additionally, among subjects with higher baseline INS, the LGI group observed a significant reduction in the 2HPP while the 2HPP levels increased in the CHDR group. This difference in 2HPP changes between groups was statistically significant (Mean ∆(LGI-CHDR) =2.4 mmol/L, P=0.004). Since interventions that reduced 2-h plasma glucose by \>0.84 mmol/L are thought to halve the risk for incidence of T2DM \[36\], LGI diets may be highly recommended for post-GDM women with higher fasting insulin levels. Furthermore, in subjects with INS≥2 μIU/L the reduction in 2HPP brought about by lowering dietary GI was not primarily mediated through body weight loss. This mechanism of action is of special interest in post-GDM women, who have little success in attaining moderate weight loss compared to other high risk groups \[1\].

The favourable anthropometric and glycaemic responses to low GI intervention in those with higher insulin levels (as against low or normal insulin secretors) can be explained by the exaggerated responses to increase in GI demonstrated among hyperinsulinaemic (insulin resistant) subjects \[14\]. While we do not possess the postprandial insulin values for our subjects to classify them as having typical hyperinsulinaemic response to a glucose challenge, an increase in fasting insulin concentrations is also associated with lower liver insulin clearance, which conserves insulin and contributes to hyperinsulinaemia \[48\]. Recent studies further corroborate the findings that dietary GI may have varying effects depending on individual metabolic functioning of the "adipo-insular axis" \[49\].

A trend for increasing weight and 2HPP blood glucose was observed in subjects with dysglycaemia within the CHDR group. Furthermore a higher likelihood of conversion to normoglycaemia among dysglycaemic subjects was observed in the LGI group. In the current trial, 37.5% and 64.3% of subjects with dysglycaemia at baseline, returned to normoglycaemia at 6 months in CHDR and LGI groups respectively. The percentage of dysglycaemic subjects returning to normoglycaemia in the LGI arm of our study was comparable to the results from lifestyle intervention in China that also used acarbose and metformin \[50\]. Hence, LGI diets could be more effective in managing glycaemia among hyperinsulinaemic, dysglycaemic women with a previous history of GDM.

We acknowledge the following limitations to the study. This study is limited by the fact that the dietary intake including GI and GL were calculated based on reported intakes, though attempts were made to ensure completeness of reporting. The 3-day food record was chosen to evaluate dietary data. This was done so since this tool is the least intrusive of diet recording techniques and was hence best suited to this group of subjects with many recognized barriers to participate in preventive interventions \[5\]. To improve the accuracy of the reporting, subjects were trained to use the three day food records at the screening visit and assisted by illustrations of household measures to aid in recording amounts consumed. Secondly, fifty- two percent of the subjects were identified as under-reporters based on a EI:BMR\<1.2, \[51\]) at baseline. However, these observations were within the estimates for prevalence of under-reporting among overweight and obese women \[52\]. Furthermore, the percentage of under-reporters in LGI and CHDR groups were comparable between groups (p=0.405). Furthermore, excluding the under-reporters did not alter the statistical significance observed in the dietary intake among subjects. Food records also do not capture details of food processing and other factors affecting dietary variables, including GI. Nevertheless, outcome changes in the LGI and CHDR groups were consistent with previous reports for similar dietary intake comparisons \[34,35\], thereby adding credence to the dietary data obtained from the subjects.

Self-reported dietary data are considered acceptable as indicators of dietary quality including percentage contribution to energy from macronutrients \[53\]. Dietary GI, being a measure of quality could also be expected to be minimally affected by underreporting. However, it is felt that underreporting may have also contributed to the smaller differences in GL observed between the groups.

It is also acknowledged that the clinically significant 10 point difference in dietary GI between the groups \[54\], could not be achieved after 6 months of intervention. Also the dietary GI for the LGI group was actually in the intermediate GI category (diet GI less than sixty \[16\]). However, more subjects in LGI had intermediate GI (62 vs. 21%), while more subjects in the CHDR group were in the high GI category (79 vs. 37%). Asian trials that achieved comparable difference in GI of around six units between groups, have also documented significant beneficial effects in terms of reductions in waist circumference, fasting blood sugar and glycaemic control in diabetic subjects or those with impaired fasting glucose \[34,35\]. This study was able to demonstrate that moderate reductions in GI of seven units had beneficial effects on the anthropometric and 2HPP outcomes of Asian post-GDM women with postpartum normoglycaemia, IFG or IGT.

We concede that neither group reached the universal 25-30 g dietary fibre intake recommendation. Achieving this target in the Malaysian environment has been recognized as a challenge \[55\]. However, it should be noted that LGI group had a significantly higher fibre intake as compared to the CHDR group in this study (17 vs. 13 g, P\<0.001). Thus, adding GI education to CHDR improved dietary fibre intakes in subjects which could not be achieved with CHDR. Such additional benefits in dietary quality when using low GI diets in the Asian population has also been documented earlier \[56\].

We do not possess formal data on satisfaction of the subjects with the two dietary interventions. However, self-reported adherence and calculated adherence to energy and fat intake prescriptions and drop-out rates were comparable between the groups. Thus it may be appropriate to consider that acceptance to both interventions may also be similar.

The assay employed to measure INS samples in this study, failed to analyse samples with INS \<2 μIU/ml. Hence the INS cut-off used to group subjects to conduct the sub-analysis to investigate the differential effect of the diets in subjects with varying insulin levels can be considered arbitrary. However, the varied metabolic response to the two diets provides a strong evidence for the added benefit of lowering GI for subjects with higher insulin levels.

# Conclusions

This six months intervention study showed that lowering the dietary GI of conventional diets improved glucose tolerance and reduced body weight, in comparison to the conventional diet in women with previous history of GDM. Subjects with higher fasting insulin level in the low GI group demonstrated the most positive effects in the improvement of their dysglycaemia and weight loss.

# Abbreviations

2HPP: 2-h post 75 g OGTT blood glucose; BMR: Basal metabolic rate; FBS: Fasting blood sugar; GDM: Gestational diabetes mellitus; GI: Glycaemic index; GL: Glycaemic load; INS: Fasting serum insulin; OGTT: Oral glucose tolerance test; T2DM: Type 2 diabetes mellitus.

# Competing interests

The authors have no potential conflict of interests to declare.

# Authors' contributions

NAK and FA conceived the project, designed the study, and were involved in data interpretation and editing of the manuscript. SS and RAG helped with study design, data collection, data analysis, interpretation and wrote the manuscript. NAW was involved in study design, data collection, and editing the manuscript. BNMY and NSS participated in designing the study, data interpretation and editing of the manuscript. KC was involved in study design, data analysis and interpretation and editing of the manuscript. All authors read and approved the final manuscript.

## Acknowledgements

Gardenia Bakeries, KL provided vouchers for low- GI Breakthru Bread for subjects in the Low GI group. This project was funded by an internal research grant from International Medical University, KL, Malaysia.


abstract: Although most epidemic human infectious diseases are caused by recently introduced pathogens, cospeciation of parasite and host is commonplace for endemic infections. Occasional host infidelity, however, provides the endemic parasite with an opportunity to survive the potential extinction of its host. Such infidelity may account for the survival of certain types of human lice, and it is currently exemplified by viruses such as HIV.
author: Robin A Weiss
date: 2009
institute: 1Division of Infection and Immunity, University College London, 46 Cleveland Street, London W1T 4JF
references:
title: Apes, lice and prehistory

Hans Zinsser's *Rats*, *Lice and History* \[1\] is a classic in microbiology. Written in 1934 and subtitled *The biography of a bacillus*, it tells the tale of that dreaded disease typhus, its reservoir in rats and its transmission among humans by lice. Here, I discuss how we may in the course of prehistory have acquired the lice, and how other infections may, like the typhus bacillus, come to be shared by us and the animal species with which we are in close contact. It is a tale of infidelity that I shall begin with the recent research on lice of David Reed and colleagues \[2,3\] and of Mark Stoneking's group \[4\] who, on the basis of phylogenetic analysis, have speculated that we may have acquired a clade of head lice from another hominid species and pubic lice from gorillas; they have also suggested that lice might help determine the date when humans adopted clothing. I shall examine this unfolding story in the context of what we know about microbial infections, and will look at the promiscuity of viruses through the lens of modern molecular technology; and I will add my own speculation on why naked apes have pubic hair.

Lice are small, wingless insects that cannot live independently from their hosts (Figure 1). They are frequent parasites of birds and mammals, each host species having its own type of louse. Humans harbor three kinds of these ectoparasites: head lice, body lice and pubic lice. For much of human history and prehistory blood-sucking lice have been so prevalent that they became part of our everyday language. We speak about feeling lousy and admonish our friends for nit-picking. Nits are the eggs of lice, expertly cemented onto hair shafts, as many parents know from painstakingly combing them out of their children's hair. Grooming among monkeys and apes is not only a means of social bonding but also a useful way of controlling nits and lice (Figure 2).

# Family heirlooms and new acquisitions

Writing on infections of humankind, Tony McMichael and I \[5\] have called those that cospeciated with their hosts 'family heirlooms' and those that crossed over from other hosts in recent evolutionary time 'new acquisitions'. The new acquisitions were initially derived from zoonotic infections but have flourished as self-sustaining infections in the human population. They have diverged from their progenitors in the original host: for example, measles is now distinct from rindepest. The majority of zoonoses, however, remain in their animal reservoirs and, so far as their sojourn in humans goes – even with limited human-to-human transfer (as with Ebola or severe acute respiratory syndrome (SARS)) – we can regard them as 'temporary exhibits'.

Human DNA might show 98% similarity to that of chimps, but we share less than 50% of our microbes and parasites with them. Ashford \[6\] argues that the great apes became more specialized forest dwellers at the same time that early hominids explored the savannah, and that human gut parasites resemble those of omnivorous baboons more than those of chimps because humans, like baboons but unlike chimps, are omnivorous. Further opportunities for horizontal crossover of microbes and parasites from animals to humans arose when humans spread out of Africa. When we domesticated ruminants, and animals such as dogs, cats and rats 'domesticated' us for the rich pickings around human habitation, we acquired many infections from our new neighbors \[5,7\]. Thus a shared habitat, rather than a shared ancestry, is important for the acquisition of many infections.

Most human pandemic infections were acquired horizontally very recently on the evolutionary timescale, even though diseases such as typhus, measles and smallpox first occurred in prehistoric times. These new acquisitions originate from evolutionarily distant host species. The influenza pandemic of 1918–1919 came from birds, and the 1968 influenza strain could be an avian-porcine recombinant. Today's novel viral infections are more likely to originate from exotic species than from animals that were domesticated long ago \[5\]. The market for 'bushmeat' has led to Ebola virus outbreaks in Africa from butchering primates, and to the SARS outbreak in China from eating small carnivores, such as civet cats. The primary reservoirs of the Ebola filovirus, the SARS coronavirus and the Nipah paramyxovirus, however, seem to be in fruit bats (flying foxes).

Lice and nits have been found in textiles, hair and combs excavated from archaeological sites \[1,8\]. Given that the closest relative of the human head and body louse, *Pediculus humanus*, is *P. schaeffi*, which infests chimpanzees, one might assume that human and chimp lice have cospeciated with their hosts as family heirlooms ever since they diverged from a common ancestor. This requires, however, that the divergence among hosts and parasites approximates to the same timescale. After all, the closest relative to human immunodeficiency virus type 1 (HIV-1) is the simian immunodeficiency virus of chimpanzees (SIVcpz), but it would be facile to suggest that HIV-1 co-evolved with humans, because molecular clock estimates place the most recent common ancestor of the pandemic form of HIV-1 at 75–100 years ago \[9,10\], and this is likely to be close to the time of the species crossover event. HIV-1 has invaded humans at least three times (groups M, N and O), and such is the power of modern forensic DNA virology that the precise location in Cameroon has been mapped for the chimpanzees carrying the SIVcpz most closely related to group M \[11,12\].

# Origins of head and body lice

Using nuclear and mitochondrial DNA markers, Reed *et al*. \[2\] estimated the divergence of chimp and human *Pediculus* lice at 5.5 million years ago (MYA) and provided evidence of cospeciation with their hosts. A recent revision to 4.1 MYA for the most recent common ancestor of chimps and humans \[13\] may require a similar adjustment of the louse molecular clock. What is more remarkable, however, is that Reed *et al*. \[2\] found that human lice split into two quite distinct clades, A and B, about 1.18 MYA. There is a worldwide clade (which includes both head and body lice) and a New World clade (exclusively head lice). So how can humans harbor two clades of louse that diverged from each other over one million years ago, when that separation is tenfold older than the emergence of *Homo sapiens*?

The answer, Reed *et al*. \[2\] suggested, is that the separation took place around the time of divergence of the ancestors of modern humans from *Homo erectus*. These two hominid lineages then co-existed for about one million years until the demise of *H. erectus*. When modern humans radiated across Asia they might have had contact with *H. erectus*, just as in more recent millennia *H. sapiens* met *H. neanderthalensis* in Europe, as dramatized by the Nobel laureate William Golding \[14\]. There is no evidence that different human species interbred, but they may well have exchanged ectoparasites. Thus, the New World clade of head louse may have crossed horizontally from *H. erectus* to *H. sapiens* within the last 100,000 years.

Zinsser \[1\] noted that the hair of ancient Peruvian mummies and the scalps of pre-Columbian Native Americans contained nits or lice. Recent DNA analysis of lice from similar remains indicates that they belong to the worldwide clade A, so this clade must have been present in pre-Columbian American populations \[15\]. A third clade of head lice has been delineated in Ethiopia and Nepal and this clade, C, diverged from clades A and B about 2 MYA \[16\]. If Reed *et al*. \[2\] were correct to postulate that clade B came from *H. erectus*, one must wonder in which hominid population might clade C lice have maintained their separate identity.

# Lice and clothing

Head and body lice used to be designated *Pediculus capitis* and *P. corporis* but they are now known to belong to the same species, *P. humanus* x\[16,17\]. Fifty years ago Levene and Dobzhansky \[18\] showed that head lice could be trained or adapted to become the rather larger body lice by attaching them to the body in small pill boxes. As we celebrate the 150th anniversary of Darwin's *Origin of Species* we might recall that it was Theodosius Dobzhansky, an eminent evolutionary biologist and a Russian Orthodox Christian, who in 1973 famously challenged creationists by declaring that "Nothing in biology makes sense except in the light of evolution." His research on lice was no exception.

Kittler *et al*. \[4\] initially reckoned that body lice diverged from head lice approximately 70,000 years ago, but they later increased this estimate to 107,000 years ago by correcting an error concerning the original outlier sequence. They postulated that this date of about 100,000 years ago coincided with or followed soon after the origin of clothing, because the naked human body is an inhospitable place for lice to breed. Head lice feed on the scalp and breed in hair, whereas body lice feed on the skin but breed in clothing.

More extensive phylogenetic analyses \[16,17\] indicate that body lice evolved from head lice several times within the worldwide clade A, as they are found in many branches of the cladisitic tree. Multiple derivations of body lice from head lice had already been considered by Zinsser \[1\], and it makes good sense if one considers that clothing was not a single invention. Wearing animal pelts fur-side next to the skin would have provided a suitable place for lice to breed before fabrics were developed with the inventions of spinning and weaving.

In 17th and 18th century Europe, most of the aristocracy and gentry shaved their hair and wore wigs. Had this custom arisen to protect them from lice as Zinsser \[1\] suggests? Not according to Samuel Pepys' diary, as he complained more than once about his wig being infested: "Thence to my barbers, to have my periwig cleared of its nits." I wonder if they were head or body lice – is a wig hair or clothing?

# Lice and nudity

Why naked apes are naked and when we 'lost' our hair has long been disputed, as discussed by Desmond Morris in *The Naked Ape* \[19\]. Rantala \[20\] suggested that nakedness could have had a selective advantage to rid the body of lice and other ectoparasites, a view also championed by Pagel and Bodmer \[21\], who added that being seen to be free of lice would be a fitness indicator and a good mating strategy. I am rather drawn to the theory first postulated by Alister Hardy \[22\] that humans evolved through an aquatic stage, although most anthropologists disparage this hypothesis. Yet Ashford \[6\] points out that several parasites specific to humans, such as three *Schistosoma* species, depend for their transmission on our entering water, which again distinguishes us from the great apes.

# Pubic lice

Pubic lice are commonly called crabs because of their appearance (Figure 1c). They belong to a different genus, *Pthirus* (a misspelling of *Phthirus* dating back to Linnaeus), from head and body lice. On the basis of morphology, human *Pthirus pubis* is closely related to the gorilla louse, *Pthirus gorillae*. In a recent paper David Reed \[3\] chose a punning Miltonian title, "Pair of lice lost or parasites regained", because it poses the conundrum of whether all the great apes had variants of both *Pediculus* and *Pthirus* and lost one or the other, or whether humans gained *Pthirus* in addition to *Pediculus*.

Molecular phylogeny indicates that human pubic lice diverged from gorilla lice as recently as 3.3 MYA \[3\], whereas the chimp and human host lineage split from the gorilla lineage at least 7 MYA (Figure 3). Thus, it seems clear that humans acquired pubic lice horizontally, possibly at the time of the *Pthirus* species' split and probably directly from gorillas. Because they were already adapted to the coarse body hair of the gorilla, crabs would have found a suitable niche in human pubic hair. Indeed, the diameter of the hair is most likely the key rather than the pubic region, because pediatric infestation of *P. pubis* is well documented: the crab is then found on the eyelashes of the infant.

# Origin of pubic hair

Reed *et al*. \[3\] suggest that the most recent common ancestor of the genera *Pediculus* and *Pthirus* was about 12.5 MYA, which is earlier than the estimated divergence of gorillas and the chimpanzee-human lineage. So was there duplication and separation of lice in the African anthropoid ape lineage, where they could have occupied separate ecological niches, rather as human head lice and pubic lice do today? Although this is an intriguing hypothesis, I was having difficulty envisioning a clear separation of habitats between the groin and other parts of our ancient common ancestor. My 'eureka moment' came, appropriately enough, in the shower: although naked apes have pubic hair, surely our hairy cousins don't?

How could I test my hypothesis? I knew that there was a stuffed chimpanzee in the Grant Zoological Museum at University College London and I called in on the way to my laboratory. Alas, he was a juvenile, which left the question open. A brisk walk across Regent's Park to inspect the adult gorillas in their splendid new pavilion at London Zoo strengthened my suspicion, and this was later confirmed by a visit to the chimpanzees at Whipsnade Zoo north of London. Indeed, as I noted previously \[23\], all the species of apes, Old World monkeys and New World monkeys seem to be less hairy in the pubic region than elsewhere; fur is present but it is short and fine.

Why do adult humans sport a thick bush of wiry pubic hair, uniquely among primates? It must surely be because we are otherwise naked. It probably serves both a visual and an odorous function, because hair aids the distribution of apocrine scent secretion, like our less visually stunning axillary hair. Unlike a beard, pubic hair is not sexually dimorphic, yet it is a feature of sexual maturation. No wonder that pubic lice are said to be the most contagious of all sexually acquired infections. Which came first, nakedness or pubic hair? I would postulate that the development of pubic hair was a consequence of the visible nakedness elsewhere on the body. Perhaps the acquisition of *P. pubis* 3.3 MYA provides the clue to when hominids developed thick pubic hair, rather as the evolution of body lice is thought to be broadly contemporaneous to the development of clothing.

It is noteworthy that the prevalence of infestation by pubic lice seems to be decreasing among women and men who remove their pubic hair using 'bikini wax', rather as the Renaissance painters discreetly depilated classical female nudes. A study from The General Infirmary, Leeds, UK, records the increasing predilection among attendants at a clinic for sexually transmitted infections to undertake extensive pubic hair waxing known as the 'Brazilian', leaving only a thin strip of hair. Armstrong and Wilson \[24\] noted a significant fall in the incidence of pubic lice among patients, although gonorrhea and chlamydia increased over the same period. Thus, there may be a health benefit to this emerging sexual lifestyle, and this finding would also lend support to the notion that nakedness protects humans from ectoparasites.

# Humans as repositories of ancient infections

Given that humans are *nouveaux riches* regarding our collection of infections \[5\], can we infer further examples of infections that could have come from other hominid species or from more distantly related primates? The infections for which we have the most accurate evolutionary record are the endogenous retroviruses that have invaded host DNA. Some 8% of the human genome represents 'fossil' integrated proviruses. The human lineage accumulated several thousand retroviral genomes after the split between New World and Old World primates, but only a handful since we diverged from chimpanzees.

Parasites that have tightly cospeciated with their hosts are, of course, in grave danger of extinction when that host becomes an endangered species. But the 'smart' parasite would gain a whole new lease of evolutionary opportunity if it engaged in occasional 'infidelity', analogous to mutation in DNA replication. A DNA lineage that does not mutate would have an extraordinarily slow rate of evolution, whereas a super-mutator without repair would provide little opportunity for natural selection before the genotype changed further. Thus, a low mutation rate within broad fidelity of DNA replication allows for both inheritance and evolution. Likewise, total cospeciation dooms the parasite to the fate of the host, whereas the ability to move horizontally to closely related hosts would provide flexibility. Parasite jumping between related hosts might occur more frequently than realized because it might easily be overlooked.

By this reckoning, the New World clade of head lice formerly faithful to the *H. erectus* lineage \[2\] adopted modern humans in the nick of time. HIV-1 might well be another successful case of jumping off a sinking ship, because its former host is not likely to survive for many generations longer in the wild. Now that HIV-1 has adopted a new host species, it is enjoying a most successful adaptive radiation and has already colonized around 60 million humans (25 million of whom have died from AIDS). Such crossover events, however, are relatively rare, and only one of the three ape-to-human transfers of HIV-1 has taken off to cause the AIDS pandemic \[11\]. It pays the host to place barriers known as restriction factors in the path of potential pathogens. If a species barrier is not recognized by the new invader or is successfully circumvented, the infection can be more virulent in the new host.

Regarding the intestinal parasites and ectoparasites that specialize in human infestation, Ashford \[6\] pointed out that we not only house two kinds of closely related lice (he meant *Pediculus* head and body lice), but also two species of *Cimex* bedbugs, two of *Demodex* mites and two of *Taenia* tapeworms. He therefore asked if we were once two separate populations that rejoined after a long separation, but Ashford did not have DNA sequences and molecular clock estimates available to him. Can we now view this phenomenon in the same way as the lice, as one of the pair of parasites cospeciating with *H. sapiens* and the other jumping from non-ancestral archaic humans to the modern human lineage? It would be intriguing to conduct similar molecular phylogenies of Ashford's other pairs.

Ashford \[6\] finished by stating: "Over to the microbiologists: What do the bacteria, viruses and fungi tell us?" There are ample examples both of cospeciation and horizontal transmission. The malaria parasite *Plasmodium falciparum* exemplifies a complex cospeciation between the parasite, its human host and its mosquito vector. *Anopheles gambiae* has also coevolved to be a specialist feeder on humans; by contrast, the other human malaria parasite, *P. vivax*, has an origin in South East Asian monkeys and is transmitted by the more promiscuous *Culex* species. Might *vivax* malaria have first adapted to *H. erectus* as an intermediate between monkeys and humans?

As a virologist, I have felt stimulated \[23\] to take up Ashford's challenge to consider pairs of related human viruses. HIV-1 and HIV-2 are very recent 20th century arrivals, from chimpanzees and sooty mangabey monkeys, respectively. With human T-cell lymphotropic viruses types 1 and 2 (HTLV-1 and HTLV-2), there have been multiple introductions of HTLV-1 from African and Asian monkeys and apes \[25\]. The provenance of HTLV-2 is puzzling, as its reservoir is in indigenous American populations and in African pygmies, which are as far apart in *H. sapiens* as one can find. Humans have five distinct polyoma viruses and multiple genital papilloma virus types. The different clades of hepatitis C virus (HCV) have deep roots but there are no known animal relatives to provide an anchor or time calibration. It would be fascinating to learn whether archaic humans harbored HCV variants, but as HCV has an RNA genome there is not much hope of gaining direct evidence by sequence amplification from ancient specimens.

All members of the herpesvirus family are thought to have strictly cospeciated with their hosts, though I have my doubts. The closest relatives to human herpes simplex virus (an α herpesvirus), cytomegalovirus (β) and Epstein-Barr virus (γ), seem to be those in the chimpanzee. Several simian species have a pair of distinct rhadinoviruses, whereas so far humans are only known to harbor one, Kaposi's sarcoma herpesvirus. On the other hand, humans have two herpes simplex viruses (HSVs), types 1 and 2. Phylogenetic analysis \[26\] indicates that HSV-1 and HSV-2 are further apart from each other than HSV-1 is from its chimp ortholog \[27\]. So where did HSV-2 come from? From its estimated age of divergence from the chimp-human HSV-1 lineage, I would place a bet on horizontal transmission from gorillas or possibly from orang-utans \[23\].

Is it a coincidence that three human parasites acquired horizontally from great apes, namely pubic lice, HIV-1 and speculatively HSV-2, are sexually transmitted? Now, before one conjures up a King Kong scenario, it should be noted that predators can pick up parasites from their prey. The close contact involved in human ancestors butchering gorillas could have enabled *Pthirus* to jump hosts, rather as bushmeat slaughter practices probably led SIVcpz and other retroviruses to invade humans from chimpanzees in modern times \[11,25\].

# Humans as a source of infections

With the advent of globalization, previously isolated human populations lost ninetenths of their number to the infections introduced by intrepid migrants and invaders \[7\]. Hernan Cortes conquered the mighty Aztec empire thanks to smallpox and measles, which the invaders inadvertently introduced to the disease-naive New World peoples \[5\]. The subsequent population crash was severe; so few indigenous people survived that the lucrative African slave trade was established in order to provide labor in the plantations. This pattern of export of Old World diseases was repeated in South America, Australia and Oceania. As Charles Darwin remarked in his diary on the voyage of the Beagle, "Wherever the European has trod death seems to pursue the Aboriginal."

It is plausible, then, that modern humans could have transmitted lethal infectious diseases to archaic human species. *H. erectus* might have given us a clade of head lice, but *H. sapiens* may have conveyed more deadly infections to *H. erectus* and later to *H. neanderthalensis*. Hard evidence is lacking, and prehistoric legends seldom tell the tale from the point of view of the vanquished, although Golding did through the eyes of the Neanderthals \[14\]. To paraphrase Darwin, wherever modern humans trod during the Pleistocene era, death seemed to pursue archaic humans. There is also a danger today that the surviving great apes may be subjected to a *coup de grace* from human infections transmitted through jungle safaris and ecotourism.

Cross-species virulence is well known. Myxamotosis resident in American cotton-tail rabbits devastated the European rabbit, and the disappearance of red squirrels in Britain wherever American gray squirrels occur is probably due to a pox virus rather than direct competition for habitat. Similarly, the α-herpesviruses that have cospeciated with Indian and African elephants cause nothing more severe than cold sores in their natural host but each seems to be lethal to the other when the two species are unnaturally housed together in zoos \[28\]. SIVcpz has little effect on chimpanzees but HIV-1 causes AIDS in humans. Thus, it might pay the host to carry a fairly harmless parasite if that infection is lethal to the host's competitors.

# Epilog

Body lice, and occasionally head and pubic lice, transmit bacterial diseases: typhus (*Rickettsia prowazekii*) \[29\], trench fever (*Bartonella quintana*) and relapsing fever (*Borellia recurrentis*). The lice themselves succumb to typhus infection but pass the Rickettsia in their feces, which the human then scratches into the skin. Typhus is known as 'war fever' and 'jail fever' because it appears in conditions where lice thrive. At the end of *Rats*, *Lice and History* Zinsser \[1\] wrote "Typhus is not dead. It will live on for centuries and will break into the open whenever human stupidity and brutality give it a chance." Sadly, Zinsser's words were prophetic. Within a few years, typhus became the major slayer in the Nazi concentration camps; typhus broke out among Rwandan refugees in Burundi in 1994, in Bosnia in 1995 and most recently in Goma.

Human brutality is another feature shared with chimpanzees that has survived in the human lineage \[30\]. It is too bad that we are not closer to the pygmy chimp (bonobo), which evolved a means of conflict resolution between troupes through alpha females engaging in lesbian sex. But that is another story.

### Acknowledgements

I am grateful to Tim Harrison and David Reed for commenting on a draft of this paper.


author: Pabulo Henrique Rampelotto
date: 2013-08-07
institute: Interdisciplinary Center for Biotechnology Research, Federal University of Pampa, Antônio Trilha Avenue, P.O.Box 1847, 97300-000, São Gabriel–RS, Brazil; E-Mail: <firstname.lastname@example.com>
title: Extremophiles and Extreme Environments

Over the last decades, scientists have been intrigued by the fascinating organisms that inhabit extreme environments. Such organisms, known as extremophiles, thrive in habitats which for other terrestrial life-forms are intolerably hostile or even lethal. They thrive in extreme hot niches, ice, and salt solutions, as well as acid and alkaline conditions; some may grow in toxic waste, organic solvents, heavy metals, or in several other habitats that were previously considered inhospitable for life. Extremophiles have been found depths of 6.7 km inside the Earth's crust, more than 10 km deep inside the ocean—at pressures of up to 110 MPa; from extreme acid (pH 0) to extreme basic conditions (pH 12.8); and from hydrothermal vents at 122 °C to frozen sea water, at −20 °C. For every extreme environmental condition investigated, a variety of organisms have shown that they not only can tolerate these conditions, but that they also often require those conditions for survival.

They are classified according to the conditions in which they grow: As thermophiles and hyperthermophiles (organisms growing at high or very high temperatures, respectively), psychrophiles (organisms that grow best at low temperatures), acidophiles and alkaliphiles (organisms optimally adapted to acidic or basic pH values, respectively), barophiles (organisms that grow best under pressure), and halophiles (organisms that require NaCl for growth). In addition, these organisms are normally polyextremophiles, being adapted to live in habitats where various physicochemical parameters reach extreme values. For example, many hot springs are acid or alkaline at the same time, and usually rich in metal content; the deep ocean is generally cold, oligotrophic (very low nutrient content), and exposed to high pressure; and several hypersaline lakes are very alkaline.

Extremophiles may be divided into two broad categories: extremophilic organisms which require one or more extreme conditions in order to grow, and extremotolerant organisms which can tolerate extreme values of one or more physicochemical parameters though growing optimally at "normal" conditions.

Extremophiles include members of all three domains of life, *i.e.*, bacteria, archaea, and eukarya. Most extremophiles are microorganisms (and a high proportion of these are archaea), but this group also includes eukaryotes such as protists (e.g., algae, fungi and protozoa) and multicellular organisms.

Archaea is the main group to thrive in extreme environments. Although members of this group are generally less versatile than bacteria and eukaryotes, they are generally quite skilled in adapting to different extreme conditions, holding frequently extremophily records. Some archaea are among the most hyperthermophilic, acidophilic, alkaliphilic, and halophilic microorganisms known. For example, the archaeal *Methanopyrus kandleri* strain 116 grows at 122 °C (252 °F, the highest recorded temperature), while the genus *Picrophilus* (e.g., *Picrophilus torridus*) include the most acidophilic organisms currently known, with the ability to grow at a pH of 0.06.

Among bacteria, the best adapted group to various extreme conditions is the cyanobacteria. They often form microbial mats with other bacteria, from Antarctic ice to continental hot springs. Cyanobacteria can also develop in hypersaline and alkaline lakes, support high metal concentrations and tolerate xerophilic conditions (*i.e.*, low availability of water), forming endolithic communities in desertic regions. However, cyanobacteria are rarely found in acidic environments at pH values lower than 5–6.

Among eukaryotes, fungi (alone or in symbiosis with cyanobacteria or algae forming lichens) are the most versatile and ecologically successful phylogenetic lineage. With the exception of hyperthermophily, they adapt well to extreme environments. Fungi live in acidic and metal-enriched waters from mining regions, alkaline conditions, hot and cold deserts, the deep ocean and in hypersaline regions such as the Dead Sea. Nevertheless, in terms of high resistance to extreme conditions, one of the most impressive eukaryotic polyextremophiles is the tardigrade, a microscopic invertebrate. Tardigrades can go into a hibernation mode, called the tun state, whereby it can survive temperatures from −272 °C (1 °C above absolute zero!) to 151 °C, vacuum conditions (imposing extreme dehydration), pressure of 6,000 atm as well as exposure to X-rays and gamma-rays. Furthermore, even active tardigrades show tolerance to some extreme environments such as extreme low temperature and high doses of radiation.

In general, the phylogenetic diversity of extremophiles is high and very complex to study. Some orders or genera contain only extremophiles, whereas other orders or genera contain both extremophiles and non-extremophiles. Interestingly, extremophiles adapted to the same extreme condition may be broadly dispersed in the phylogenetic tree of life. This is the case for different psychrophiles or barophiles, for which members may be found dispersed in the three domains of life. There are also groups of organisms belonging to the same phylogenetic family that have adapted to very diverse extreme or moderately extreme conditions.

Over the last few decades, the fast development of molecular biology techniques has led to significant advances in the field, allowing us to investigate intriguing questions on the nature of extremophiles with unprecedented precision. In particular, new high-throughput DNA sequencing technologies have revolutionized how we explore extreme microbiology, revealing microbial ecosystems with unexpectedly high levels of diversity and complexity. Nevertheless, a thorough knowledge of the physiology of organisms in culture is essential to complement genomic or transcriptomic studies and cannot be replaced by any other approach. Consequently, the combination of improved traditional methods of isolation/cultivation and modern culture-independent techniques may be considered the best approach towards a better understanding of how microorganisms survive and function in such extreme environments.

Based on such technological advances, the study of extremophiles has provided, over the last few years, ground-breaking discoveries that challenge the paradigms of modern biology and make us rethink intriguing questions such as "what is life?", "what are the limits of life?", and "what are the fundamental features of life?". These findings have made the study of life in extreme environments one of the most exciting areas of research, and can tell us much about the fundaments of life.

The mechanisms by which different organisms adapt to extreme environments provide a unique perspective on the fundamental characteristics of biological processes, such as the biochemical limits to macromolecular stability and the genetic instructions for constructing macromolecules that stabilize in one or more extreme conditions. These organisms present a wide and versatile metabolic diversity coupled with extraordinary physiological capacities to colonize extreme environments. In addition to the familiar metabolic pathway of photosynthesis, extremophiles possess metabolisms based upon methane, sulfur, and even iron.

Although the molecular strategies employed for survival in such environments are still not fully clarified, it is known that these organisms have adapted biomolecules and peculiar biochemical pathways which are of great interest for biotechnological purposes. Their stability and activity at extreme conditions make them useful alternatives to labile mesophilic molecules. This is particularly true for their enzymes, which remain catalytically active under extremes of temperature, salinity, pH, and solvent conditions. Interestingly, some of these enzymes display polyextremophilicity (*i.e.,* stability and activity in more than one extreme condition) that make their wide use in industrial biotechnology possible.

From an evolutionary and phylogenetic perspective, an important achievement that has emerged from studies involving extremophiles is that some of these organisms form a cluster on the base of the tree of life. Many extremophiles, in particular the hyperthermophiles, lie close to the "universal ancestor" of all organisms on Earth. For this reason, extremophiles are critical for evolutionary studies related to the origins of life. It is also important to point out that the third domain of life, the archaea, was discovered partly due to the first studies on extremophiles, with profound consequences for evolutionary biology.

Furthermore, the study of extreme environments has become a key area of research for astrobiology. Understanding the biology of extremophiles and their ecosystems permits developing hypotheses regarding the conditions required for the origin and evolution of life elsewhere in the universe. Consequently, extremophiles may be considered as model organisms when exploring the existence of extraterrestrial life in planets and moons of the Solar System and beyond. For example, the microorganisms discovered in ice cores recovered from the depth of the Lake Vostok and other perennially subglacial lakes from Antarctica may serve as models for the search of life in the Jupiter's moon Europa. Microbial ecosystems found in extreme environments like the Atacama Desert, the Antarctic Dry Valleys and the Rio Tinto may be analogous to potential life forms adapted to Martian conditions. Likewise, hyperthermophilic microorganisms present in hot springs, hydrothermal vents and other sites heated by volcanic activity in terrestrial or marine areas may resemble potential life forms existing in other extraterrestrial environments. Recently, the introduction of novel techniques such as Raman spectroscopy into the search of life signs using extremophilic organisms as models has open further perspectives that might be very useful in astrobiology.

With these groundbreaking discoveries and recent advances in the world of exthemophiles, which have profound implications for different branches of life sciences, our knowledge about the biosphere has grown and the putative boundaries of life have expanded. However, despite the latest advances we are just at the beginning of exploring and characterizing the world of extremophiles. This special issue discusses several aspects of these fascinating organisms, exploring their habitats, biodiversity, ecology, evolution, genetics, biochemistry, and biotechnological applications in a collection of exciting reviews and original articles written by leading experts and research groups in the field. I would like to thank the authors and co-authors for submitting such interesting contributions. I also thank the Editorial Office and numerous reviewers for their valuable assistance in reviewing the manuscripts.

## Conflict of Interest

The authors declare no conflict of interest.