BACKGROUND Considerable uncertainty exists as to whether lowering low-density lipoprotein cholesterol (LDL-C) by inhibiting the Niemann-Pick C1-Like 1 (NPC1L1) receptor with ezetimibe, either alone or in combination with a 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) inhibitor (statin), will reduce the risk of coronary heart disease (CHD). OBJECTIVES This study evaluated the effect of naturally random allocation to lower LDL-C mediated by polymorphisms in the NPC1L1 gene (target of ezetimibe), the HMGCR gene (target of statins), or both (target of combination therapy) on the risk of CHD. METHODS We constructed NPC1L1 and HMGCR genetic LDL-C scores to naturally randomize participants into 4 groups: reference, lower LDL-C mediated by NPC1L1 polymorphisms, lower LDL-C mediated by HMGCR polymorphisms, or lower LDL-C mediated by polymorphisms in both NPC1L1 and HMGCR. We compared the risk of CHD (fatal or nonfatal myocardial infarction) among each group using a 2 × 2 factorial mendelian randomization study design. RESULTS A total of 108,376 persons (10,464 CHD events) from 14 studies were included. There were no significant differences in baseline characteristics among the 4 groups, thus confirming that allocation was random. Compared to the reference group, the NPC1L1 group had 2.4 mg/dl lower LDL-C and 4.8% lower risk of CHD (odds ratio [OR]: 0.952, 95% confidence interval [CI]: 0.920 to 0.985); whereas the HMGCR group had 2.9 mg/dl lower LDL-C and a similar 5.3% lower risk of CHD (OR: 0.947, 95% CI: 0.909 to 0.986). The group with lower LDL-C mediated by both NPC1L1 and HMGCR polymorphisms had 5.8 mg/dl additively lower LDL-C and a 10.8% log-linearly additive lower risk of CHD (OR: 0.892, 95% CI: 0.854 to 0.932). CONCLUSIONS The effect of lower LDL-C on the risk of CHD mediated by polymorphisms in NPC1L1, HMGCR, or both is approximately the same per unit lower LDL-C and log-linearly proportional to the absolute exposure to lower LDL-C.

A major goal of biomedicine is to understand the function of every gene in the human genome.1 Loss-of-function (LoF) mutations can disrupt both copies of a given gene in humans and phenotypic analysis of such ‘human knockouts’ can provide insight into gene function. Consanguineous unions are more likely to result in offspring who carry LoF mutations in a homozygous state. In Pakistan, consanguinity rates are notably high.2 Here, we sequenced the protein-coding regions of 10,503 adult participants in the Pakistan Risk of Myocardial Infarction Study (PROMIS) designed to understand the determinants of cardiometabolic diseases in South Asians.3 We identified individuals carrying predicted LoF (pLoF) mutations in the homozygous state, and performed phenotypic analysis involving >200 biochemical and disease traits. We enumerated 49,138 rare (<1 % minor allele frequency) pLoF mutations. These pLoF mutations are predicted to knock out 1,317 genes in at least one participant. Homozygosity for pLoF mutations at PLAG27 was associated with absent enzymatic activity of soluble lipoprotein-associated phospholipase A2; at CYP2F1, with higher plasma interleukin-8 concentrations; at TREH, with lower concentrations of apoB-containing lipoprotein subfractions; at either A3GALT2 or NRG4, with markedly reduced plasma insulin C-peptide concentrations; and at SLC9A3R1, with mediators of calcium and phosphate signaling. Finally, APOC3 is a gene which retards clearance of plasma triglyceride-rich lipoproteins and where heterozygous deficiency confers protection against coronary heart disease.4,5 In Pakistan, we now observe APOC3 homozygous pLoF carriers; we recalled these knockout humans and challenged with an oral fat load. Compared with wild-type family members, APOC3 knockouts displayed marked blunting of the usual post-prandial rise in plasma triglycerides. Overall, these observations provide a roadmap for a ‘human knockout project’, a systematic effort to understand the phenotypic consequences of complete disruption of genes in humans.

To evaluate the shared genetic etiology of type-2 diabetes (T2D) and coronary heart disease (CHD), we conducted a multi-ethnic study of genetic variation genome-wide for both diseases in up to 265,678 subjects for T2D and 260,365 subjects for CHD. We identify 16 previously unreported loci for T2D and one for CHD, including a novel T2D association at a missense variant in HLA-DRB5 (OR=1.29). We show that genetically mediated increase in T2D risk also confers higher CHD risk. Joint analysis of T2D loci demonstrated that 24% are associated with CHD, highlighting eight variants - two of which are coding - where T2D and CHD associations appear to co-localize, and a novel joint T2D/CHD association which also replicated for T2D. Variants associated with both outcomes implicate several novel pathways including cellular proliferation and cardiovascular development.

SummaryBackgroundThe lipoprotein(a) pathway is a causal factor in coronary heart disease. We used a genetic approach to distinguish the relevance of two distinct components of this pathway, apolipoprotein(a) isoform size and circulating lipoprotein(a) concentration, to coronary heart disease.MethodsIn this mendelian randomisation study, we measured lipoprotein(a) concentration and determined apolipoprotein(a) isoform size with a genetic method (kringle IV type 2 [KIV2] repeats in the LPA gene) and a serum-based electrophoretic assay in patients and controls (frequency matched for age and sex) from the Pakistan Risk of Myocardial Infarction Study (PROMIS). We calculated odds ratios (ORs) for myocardial infarction per 1-SD difference in either LPA KIV2 repeats or lipoprotein(a) concentration. In a genome-wide analysis of up to 17 503 participants in PROMIS, we identified genetic variants associated with either apolipoprotein(a) isoform size or lipoprotein(a) concentration. Using a mendelian randomisation study design and genetic data on 60 801 patients with coronary heart disease and 123 504 controls from the CARDIoGRAMplusC4D consortium, we calculated ORs for myocardial infarction with variants that produced similar differences in either apolipoprotein(a) isoform size in serum or lipoprotein(a) concentration. Finally, we compared phenotypic versus genotypic ORs to estimate whether apolipoprotein(a) isoform size, lipoprotein(a) concentration, or both were causally associated with coronary heart disease.FindingsThe PROMIS cohort included 9015 patients with acute myocardial infarction and 8629 matched controls. In participants for whom KIV2 repeat and lipoprotein(a) data were available, the OR for myocardial infarction was 0·93 (95% CI 0·90–0·97; p<0·0001) per 1-SD increment in LPA KIV2 repeats after adjustment for lipoprotein(a) concentration and conventional lipid concentrations. The OR for myocardial infarction was 1·10 (1·05–1·14; p<0·0001) per 1-SD increment in lipoprotein(a) concentration, after adjustment for LPA KIV2 repeats and conventional lipids. Genome-wide analysis identified rs2457564 as a variant associated with smaller apolipoprotein(a) isoform size, but not lipoprotein(a) concentration, and rs3777392 as a variant associated with lipoprotein(a) concentration, but not apolipoprotein(a) isoform size. In 60 801 patients with coronary heart disease and 123 504 controls, OR for myocardial infarction was 0·96 (0·94–0·98; p<0·0001) per 1-SD increment in apolipoprotein(a) protein isoform size in serum due to rs2457564, which was directionally concordant with the OR observed in PROMIS for a similar change. The OR for myocardial infarction was 1·27 (1·07–1·50; p=0·007) per 1-SD increment in lipoprotein(a) concentration due to rs3777392, which was directionally concordant with the OR observed for a similar change in PROMIS.InterpretationHuman genetic data suggest that both smaller apolipoprotein(a) isoform size and increased lipoprotein(a) concentration are independent and causal risk factors for coronary heart ...

Key Points Question Did the delivery of services within a cancer system change during the first year of the COVID-19 pandemic? Findings This population-based cohort study conducted in Ontario, Canada, found a total of 4 476 693 cancer care services during the first year of the COVID-19 pandemic, compared with 5 644 105 services in the year prior, representing a reduction of 20.7% and suggesting a backlog of 1 167 412 cancer services during the first pandemic year. Limited change was observed in systemic treatments and emergency or urgent imaging examinations and surgical procedures, while major reductions were observed in cancer screening tests, biopsies, surgical treatments, and new consultations for systemic and radiation treatment. Meaning These findings provide evidence on the deficits in cancer care that occurred during the first year of the COVID-19 pandemic that are likely to inform continued delivery of care, recovery, and future pandemic planning.