Hong Pan

Background: Cardiometabolic diseases arise from metabolic dysfunction that develops decades before clinical onset. Conventional genetic risk models are typically derived in middle-aged or older populations, where genetic effects are confounded by cumulative environmental exposures, chronic comorbidities, and clinical interventions. Whether the life stage at which genetic liability is modelled influences the biological signal captured by polygenic scores remains unclear, particularly in underrepresented populations. We therefore tested whether genetic liability modelled in early adulthood, a period of relative physiological stability, is associated with cardiometabolic risk across the life course in Asian populations. Methods: We developed a polygenic score for metabolic syndrome, GenMetS, using data from 1,368 Singaporean women aged 18-45 years. The model integrates 15 established polygenic scores for metabolic traits and applies elastic-net penalized regression to optimize variant weights. GenMetS was evaluated in five cohorts comprising 670,952 individuals aged 0-94 years across population-based and disease-enriched settings, including Asian and European ancestry groups. Associations with metabolic traits, cardiometabolic diseases, multimorbidity, and early-life growth patterns were assessed. Results: In Asian populations, GenMetS explained 5.0-12.4% of the variance in metabolic syndrome in adults and 10.3% in children, with negligible performance in European populations (R squared < 0.001). Higher GenMetS was associated with increased odds of cardiometabolic diseases, including type 2 diabetes, heart failure, and stroke (odds ratios 1.32-1.52 per standard deviation). In UK Biobank participants of Asian ancestry, GenMetS improved discrimination of cardiometabolic multimorbidity beyond age alone. Associations were consistent across sexes. In children, higher GenMetS was associated with obesogenic growth trajectories and increased abdominal adiposity. Conclusions: Genetic liability to metabolic dysfunction modelled in early adulthood captures a stable biological signal associated with metabolic traits, disease risk, and multimorbidity from childhood to adulthood in Asian populations. These findings indicate that the life stage of model derivation shapes the biological signal captured by polygenic scores and support the development of life-stage and ancestry-informed approaches for cardiometabolic risk assessment and prevention.

Background: Variants in the ATP binding cassette protein subfamily D member 1 (ABCD1) gene are known to cause X‐linked adrenoleukodystrophy (X‐ALD). This study focused on the characteristics of ABCD1 variants in Chinese X‐ALD families and elucidated the value of genetic approaches for X‐ALD.Methods: 68 male probands diagnosed as X‐ALD were screened for ABCD1 variants by the Sanger sequencing of polymerase chain reaction (PCR) products and multiplex ligation‐dependent probe amplification (MLPA) combined with long‐range PCR. Prenatal diagnosis was performed in 20 foetuses of 17 probands’ mothers. Descriptive statistics were used to summarise the gene variants and prenatal diagnosis characteristics and outcomes.Results: This study allowed the identification of 61 variants occurring in 68 families, including 58 single nucleotide variants or small deletion/insertion variants and 3 large deletions. Three probands with no variants detected by next‐generation sequencing were found to have variants by PCR‐sequencing. Prenatal diagnosis found that 10 of the 20 foetuses had no variants in ABCD1.Conclusion: PCR primers that do not amplify the pseudogenes must be used for PCR‐sequencing. MLPA combined with long‐range PCR can detect large deletions and insertions, which are usually undetectable by PCR‐sequencing. Prenatal diagnosis could help to prevent the birth of infants with X‐ALD.