Edmund Chan

Exome sequencing of 20,791 cases of type 2 diabetes and 24,440 controls Protein-coding genetic variants that strongly affect disease risk can yield relevant clues to disease pathogenesis. Here we report exome-sequencing analyses of 20,791 individuals with type 2 diabetes (T2D) and 24,440 non-diabetic control participants from 5 ancestries. We identify gene-level associations of rare variants (with minor allele frequencies of less than 0.5%) in 4 genes at exome-wide significance, including a series of more than 30 SLC30A8 alleles that conveys protection against T2D, and in 12 gene sets, including those corresponding to T2D drug targets (P = 6.1 10 -3 ) and candidate genes from knockout mice (P = 5.2 10 -3 ). Within our study, the strongest T2D gene-level signals for rare variants explain at most 25% of the heritability of the strongest common single-variant signals, and the gene-level effect sizes of the rare variants that we observed in established T2D drug targets will require 75,000-185,000 sequenced cases to achieve exome-wide significance. We propose a method to interpret these modest rare-variant associations and to incorporate these associations into future target or gene prioritization efforts.

Hundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier develops the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we apply clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias display effect sizes significantly larger than the top 1% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers average 60% or lower for most conditions. We assess epidemiologic and genetic factors contributing to risk prediction in monogenic variant carriers, demonstrating that inclusion of polygenic variation significantly improves biomarker estimation for two monogenic dyslipidemias.

CONTEXT: Isolated elevation of TSH in the absence of thyroid symptoms can be very rarely caused by a macromolecule formed between TSH and Ig (macro-TSH), confounding the interpretation of thyroid function test results. OBJECTIVE: We described the use of several commonly available laboratory-based approaches to investigate an isolated TSH elevation [232 mIU/liter; free T(4), 10 pmol/liter (reference interval, 10.0-23.0 pmol/liter), Vitros platform] in a clinically euthyroid elderly gentleman, which led to the diagnosis of macro-TSH. METHODS AND RESULTS: TSH concentration of the patient was significantly lower (122 mIU/liter) when measured on the Advia Centaur platform. Serial dilution of the patient's sample showed a nonlinear increase in TSH recovery at increasing dilution (nonlinearity). Polyethylene glycol precipitation and mixing the patient's sample with a hypothyroid patient sample showed reduced TSH recovery, suggesting the presence of a high molecular weight interfering substance and excess TSH binding capacity, respectively. Heterophile blocking tube studies and rheumatoid factors were negative. Gel filtration chromatography demonstrated a TSH peak fraction that approximated the molecular size of IgG; together with the excess TSH binding capacity, this indicated the presence of TSH-IgG macro-TSH. A review of 12 macro-TSH case reports showed that samples with macro-TSH produce over-recovery with dilution, return negative results on anti-animal and anti-heterophile blocking studies, and commonly have recovery of less than 20% when subjected to polyethylene glycol precipitation. CONCLUSION: Macro-TSH is an underrecognized laboratory interference. Routine laboratory techniques described above can help diagnose this rare entity. A close dialogue between the physician and the laboratory is important in approaching such cases.

Large-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency < 1%) predicted damaging coding variation by using sequence data from >170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels; some of these genes have not been previously associated with lipid levels when using rare coding variation from population-based samples. We prioritize 32 genes in array-based genome-wide association study (GWAS) loci based on aggregations of rare coding variants; three (EVI5, SH2B3, and PLIN1) had no prior association of rare coding variants with lipid levels. Most of our associated genes showed evidence of association among multiple ancestries. Finally, we observed an enrichment of gene-based associations for low-density lipoprotein cholesterol drug target genes and for genes closest to GWAS index single-nucleotide polymorphisms (SNPs). Our results demonstrate that gene-based associations can be beneficial for drug target development and provide evidence that the gene closest to the array-based GWAS index SNP is often the functional gene for blood lipid levels.

The Singapore population comprises Chinese, Malays and Asian Indians. Within this population, Asian Indians have the highest rates of coronary heart disease, whereas Chinese have the lowest. Conversely, Indians have the lowest high-density lipoprotein cholesterol (HDL-C) concentrations, followed by Malays and Chinese. We studied the TaqIB and -629C>A polymorphisms at the CETP locus in 1300 Chinese, 364 Malay and 282 Asian Indian men, and in 1558 Chinese, 397 Malay and 306 Asian Indian women, to determine whether these polymorphisms are responsible for the ethnic difference in HDL-C concentration. The frequency of the B2 allele in Chinese, Malays and Indians was 0.384, 0.339 and 0.449 in men, and 0.379, 0.329 and 0.415 in women, respectively (p < 0.001). For the A-629 allele, the relative frequencies were 0.477, 0.423 and 0.592 in men and 0.486, 0.416 and 0.575 in women (p < 0.001). The two polymorphisms were in linkage disequilibrium (D / Dmax= 0.9772, p < 0.00001). The B2 and the A-629 alleles were associated with increased HDL-C concentrations in a dose-dependent manner. The B2 allele continued to show an association with HDL-C concentration, even after controlling for the genotype at position -629. Dietary cholesterol showed a significant interaction with the TaqIB polymorphism in determining HDL-C concentrations in Indians and Malays, but not in Chinese. In conclusion, the high frequencies of these polymorphisms in Asian Indians could not explain the observed ethnic differences in HDL-C concentration. Moreover, we observed an ethnic-specific interaction among dietary cholesterol, the TaqIB polymorphism and HDL-C concentrations.