STUDY MATERIALS: The investigators have finished the latest data collection performed at age 63 in 2021-2022 of the human longitudinal cohort study SPAF-1958. At baseline, in 1974, six geographic areas in Sweden were systematically selected. In each area, one upper secondary school was randomly selected, from which 429 (224 male, and 205 female) pupils in the lowest grade level were randomly selected to be included in the study. The entire cohort was invited for questionnaire and testing at age 16, 34 and 52 and 63 years. DATA COLLECTION: Questionnaire: The questionnaire included questions about lifestyle factors such as physical activity, dietary habits, smoking, alcohol consumption.

The questionnaire also included questions about health, disease, medication, and personal traits. Testing of physical performance: Some tests for physical performance were used at all data collections from 16 to 63 years, including aerobic capacity and muscle static and dynamic strength. Specific tests assessing muscle function in relation to muscle weakness were added to the testing at 63 years. Venous blood was drawn for analysis of standard health variables as well as extended studying of endocrine profile and inflammatory cell profile. The muscle size of two selected muscles on the leg were estimated by ultrasound. Body composition and muscle size were determined in 60 subjects by MR imaging of the whole body. Testing of neurological status: Motor nerve conductions studies (NCS) were performed on the right median and ulnar, and bilaterally on tibial, and peroneal nerves. Sensory NCS were performed on the right median, ulnar, and superficial radial nerves, and bilaterally on the sural and superficial peroneal nerves. Motor and sensory conduction velocities, proximal and distal compound muscle action potentials (CMAP), and sensory nerve action potentials (SNAP) were recorded. For motor unit number estimation (MUNE) m. tibialis anterior (TA) and m. abductor policies brevis (ABP) were tested by electrical stimulation of the median and peroneal nerve, respectively. MUNE was obtained by dividing the size of the maximal CMAP by the size of the mean surface-recorded single motor unit potential (S-MUP). MUNE=Max CMAP (area) / Mean SMUP (area). To define small fibre neuropathy a skin biopsy was collected to measure the density of small fibre epidermal innervation. Skeletal muscle samples were obtained with a Bergström biopsy needle from m. vastus lateralis and were snap-frozen in liquid nitrogen cooled isopentane and stored at -80°C. To maximize the possibility to include high number of neuromuscular transmission junctions (endplates) in the muscle biopsy, the optimal biopsy site was determined by location of maximal twitch response to electrical nerve stimulation. Furthermore, the needle was re-directed after penetration of the skin to cut myofibers as longitudinally as possible. This approach was chosen to optimize the conditions for analyses of the NMJ.

ANALYSES OF SKELETAL MUSCLE: The data collection at 63 years will be completed with morphological and immune-/enzyme-histochemical analysis of 120 muscle biopsies. Disruption of axon and motor unit integrity may initiate and drive the wasting and functional impairment of skeletal muscles during aging. To test our hypothesis of the neurogenic impact on loss of muscle strength, the investigators will examine and compare biopsies of skeletal muscle from age 27 and 63 in the same individuals. This part of the analyses will focus on fibre type transitions (myosin subtypes), change in fibre-size and clustering of fibre types with advancing age (a sign of denervation followed by re-innervation). For the biopsies at age 63, after cryo-sectioning, muscle sections will be stained using enzyme histochemistry, histological stains, and immunohistochemistry, followed by confocal microscopy imaging. From 27 years of age there are sectioned and stained muscle tissue available from a subgroup of the cohort, to compare with the characteristics of the muscle at 63 years. These samples need to be digitalised in our microscopy and imaging analysis facility before analyses of fibre clustering. Also, the muscle biopsies harvested at age 63 will be analysed for NMJ by staining for acetylcholine (presynaptic), CHARNs (postsynaptic receptors), terminal Schwann cells, and the parallel autonomic innervation (norepinephrine). The investigators will use a panel of antibodies including markers of axonal and terminal Schwann cell involvement in re-innervation. The cryo-sectioning and refinement/validation of the labelling protocols will be performed by HR in collaboration with BU, TG and MW. HR has a full-time position in the group and is specialized in these methods. In addition, the investigators apply for funding 1 month for a research assistant to digitalise and analyse muscle fibre composition from age 27. ANALYSES OF MAGNETIC RESONANCE IMAGES Subjects have been scanned with a 1.5 Tesla Siemens camera at Karolinska University Hospital in Huddinge. The investigators used a modified 2-point Dixon fat-water sequence that scans the entire body in 6 minutes. Automatic image analysis will be performed using AMRA™ segmentation software (Advanced MR Analytics AB, Linköping, Sweden). The data provided include adipose and muscle tissue of the entire body (from neck to knee), muscle volume and muscle fat infiltration in the anterior and posterior thigh muscles, and subcutaneous adipose tissue in the abdomen and fat content of the liver. The advantage of the results of the MRI technique is not only the very high reproducibility, but also the fact that it can be adjusted to body size using muscle-specific z-scores for volume and fat infiltration. This has been a major problem in the past, as essentially small people were much more easily classified as sarcopenic, while overweight/obese people were rarely classified as having too little muscle mass. The standardized z-score has been calculated for different age groups based on over 10 000 people scanned in the UK Biobank. Both muscle volume value and fat infiltration of muscle were associated with physical function, with the strongest predictive value when low muscle volume was combined with high fat infiltration, i.e. adverse muscle composition.