Early detection has the potential to reduce cancer mortality, but an effective screening test must demonstrate asymptomatic cancer detection years before conventional diagnosis in a longitudinal study. In the Taizhou Longitudinal Study (TZL), 123,115 healthy subjects provided plasma samples for long-term storage and were then monitored for cancer occurrence. Here we report the preliminary results of PanSeer, a noninvasive blood test based on circulating tumor DNA methylation, on TZL plasma samples from 605 asymptomatic individuals, 191 of whom were later diagnosed with stomach, esophageal, colorectal, lung or liver cancer within four years of blood draw. We also assay plasma samples from an additional 223 cancer patients, plus 200 primary tumor and normal tissues. We show that PanSeer detects five common types of cancer in 88% (95% CI: 80–93%) of post-diagnosis patients with a specificity of 96% (95% CI: 93–98%), We also demonstrate that PanSeer detects cancer in 95% (95% CI: 89–98%) of asymptomatic individuals who were later diagnosed, though future longitudinal studies are required to confirm this result. These results demonstrate that cancer can be non-invasively detected up to four years before current standard of care.

There is increasing evidence showing that the dynamic changes in the gut microbiota can alter brain physiology and behavior. Cognition was originally thought to be regulated only by the central nervous system. However, it is now becoming clear that many non-nervous system factors, including the gut-resident bacteria of the gastrointestinal tract, regulate and influence cognitive dysfunction as well as the process of neurodegeneration and cerebrovascular diseases. Extrinsic and intrinsic factors including dietary habits can regulate the composition of the microbiota. Microbes release metabolites and microbiota-derived molecules to further trigger host-derived cytokines and inflammation in the central nervous system, which contribute greatly to the pathogenesis of host brain disorders such as pain, depression, anxiety, autism, Alzheimer’s diseases, Parkinson’s disease, and stroke. Change of blood–brain barrier permeability, brain vascular physiology, and brain structure are among the most critical causes of the development of downstream neurological dysfunction. In this review, we will discuss the following parts: Overview of technical approaches used in gut microbiome studies Microbiota and immunity Gut microbiota and metabolites Microbiota-induced blood–brain barrier dysfunction Neuropsychiatric diseases ■ Stress and depression ■ Pain and migraine ■ Autism spectrum disorders Neurodegenerative diseases ■ Parkinson’s disease ■ Alzheimer’s disease ■ Amyotrophic lateral sclerosis ■ Multiple sclerosis Cerebrovascular disease ■ Atherosclerosis ■ Stroke ■ Arteriovenous malformation Conclusions and perspectives

Genetic studies of Tibetans, an ethnic group with a long-lasting presence on the Tibetan Plateau which is known as the highest plateau in the world, may offer a unique opportunity to understand the biological adaptations of human beings to high-altitude environments. We conducted a genome-wide study of 1,000,000 genetic variants in 46 Tibetans (TBN) and 92 Han Chinese (HAN) for identifying the signals of high-altitude adaptations (HAAs) in Tibetan genomes. We discovered the most differentiated variants between TBN and HAN at chromosome 1q42.2 and 2p21. EGLN1 (or HIFPH2, MIM 606425) and EPAS1 (or HIF2A, MIM 603349), both related to hypoxia-inducible factor, were found most differentiated in the two regions, respectively. Strong positive correlations were also observed between the frequency of TBN-dominant haplotypes in the two gene regions and altitude in East Asian populations. Linkage disequilibrium and further haplotype network analyses of world-wide populations suggested the antiquity of the TBN-dominant haplotypes and long-term persistence of the natural selection. Finally, a “dominant haplotype carrier” hypothesis could describe the role of the two genes in HAA. All of our population genomic and statistical analyses indicate that EPAS1 and EGLN1 are most likely responsible for HAA of Tibetans. Interestingly, one each but not both of the two genes were also identified by three recent studies. We reanalyzed the available data and found the escaped top signal (EPAS1) could be recaptured with data quality control and our approaches. Based on this experience, we call for more attention to be paid to controlling data quality and batch effects introduced in public data integration. Our results also suggest limitations of extended haplotype homozygosity-based method due to its compromised power in case the natural selection initiated long time ago and particularly in genomic regions with recombination hotspots.

Premature ovarian insufficiency (POI) is a major cause of female infertility due to early loss of ovarian function. POI is a heterogeneous condition, and its molecular etiology is unclear. To identify genetic variants associated with POI, here we performed whole-exome sequencing in a cohort of 1,030 patients with POI. We detected 195 pathogenic/likely pathogenic variants in 59 known POI-causative genes, accounting for 193 (18.7%) cases. Association analyses comparing the POI cohort with a control cohort of 5,000 individuals without POI identified 20 further POI-associated genes with a significantly higher burden of loss-of-function variants. Functional annotations of these novel 20 genes indicated their involvement in ovarian development and function, including gonadogenesis (LGR4 and PRDM1), meiosis (CPEB1, KASH5, MCMDC2, MEIOSIN, NUP43, RFWD3, SHOC1, SLX4 and STRA8) and folliculogenesis and ovulation (ALOX12, BMP6, H1-8, HMMR, HSD17B1, MST1R, PPM1B, ZAR1 and ZP3). Cumulatively, pathogenic and likely pathogenic variants in known POI-causative and novel POI-associated genes contributed to 242 (23.5%) cases. Further genotype–phenotype correlation analyses indicated that genetic contribution was higher in cases with primary amenorrhea compared to that in cases with secondary amenorrhea. This study expands understanding of the genetic landscape underlying POI and presents insights that have the potential to improve the utility of diagnostic genetic screenings.