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Alzheimer's disease is a genetically complex disorder; rare variants in the triggering receptor expressed on myeloid cells 2 (TREM2) gene have been shown to as much as triple an individual's risk of developing Alzheimer's disease. TREM2 is a transmembrane receptor expressed in cells of the myeloid lineage, and its association with Alzheimer's disease supports the involvement of immune and inflammatory pathways in the cause of the disease, rather than as a consequence of the disease. TREM2 variants associated with Alzheimer's disease induce partial loss of function of the TREM2 protein and alter the behaviour of microglial cells, including their response to amyloid plaques. TREM2 variants have also been shown to cause polycystic lipomembranous osteodysplasia with sclerosing leukoencephalopathy and frontotemporal dementia. Although the low frequency of TREM2 variants makes it difficult to establish robust genotype–phenotype correlations, such studies are essential to enable a comprehensive understanding of the role of TREM2 in different neurological diseases, with the ultimate goal of developing novel therapeutic approaches.

In just over a decade, advances in genome-wide association studies (GWAS) have offered an approach to stratify individuals based on genetic risk for disease. Using recent Alzheimer's disease (AD) GWAS results as the base data, we determined each individual's polygenic risk score (PRS) in the UK Biobank dataset. Using individuals within the extreme risk distribution, we performed a GWAS that is agnostic of AD phenotype and is instead based on known genetic risk for disease. To interpret the functions of the new risk factors, we conducted phenotype analyses, including a phenome-wide association study. We identified 246 loci surpassing the significance threshold of which 229 were not reported in the base AD GWAS. These include loci that showed suggestive levels of association in the base GWAS and loci not previously suspected to be associated with AD. Among these, there are loci, such as IL34 and KANSL1 , that have since been shown to be associated with AD in recent studies. We also show highly significant genetic correlations with multiple health-related outcomes that provide insights into prodromal symptoms and comorbidities. This is the first study to utilize PRS as a phenotype-agnostic group classification in AD genetic studies. We identify potential new loci for AD and detail phenotypic analysis of these PRS extremes.

The search for rare variants in Alzheimer’s disease (AD) is usually deemed a high-risk - high-reward situation. The challenges associated with this endeavor are real. Still, the application of genome-wide technologies to large numbers of cases and controls or to small, well-characterized families has started to be fruitful. Rare variants associated with AD have been shown to increase risk or cause disease, but also to protect against the development of AD. All of these can potentially be targeted for the development of new drugs. Multiple independent studies have now shown associations of rare variants in NOTCH3 , TREM2 , SORL1 , ABCA7 , BIN1 , CLU , NCK2 , AKAP9 , UNC5C , PLCG2, and ABI3 with AD and suggested that they may influence disease via multiple mechanisms. These genes have reported functions in the immune system, lipid metabolism, synaptic plasticity, and apoptosis. However, the main pathway emerging from the collective of genes harboring rare variants associated with AD is the Aβ pathway. Associations of rare variants in dozens of other genes have also been proposed, but have not yet been replicated in independent studies. Replication of this type of findings is one of the challenges associated with studying rare variants in complex diseases, such as AD. In this review, we discuss some of these primary challenges as well as possible solutions. Integrative approaches, the availability of large datasets and databases, and the development of new analytical methodologies will continue to produce new genes harboring rare variability impacting AD. In the future, more extensive and more diverse genetic studies, as well as studies of deeply characterized families, will enhance our understanding of disease pathogenesis and put us on the correct path for the development of successful drugs.

Key Points New sequencing technologies have allowed the examination of genetic variability at unprecedented resolution and scale. From testing millions of known markers in thousands of individuals to identifying very rare or novel mutations in smaller cohorts, these technologies have changed how genetics can inform disease phenotype. Whole-genome genotyping has allowed genome-wide association studies to be performed, which have greatly increased our knowledge of how genetics plays a role in common diseases. It is also an efficient method for performing homozygosity mapping to pinpoint pathogenic mutations in recessive kindreds. Whole-exome sequencing has allowed the rapid and cost-effective identification of Mendelian genes. This point is clearly illustrated by the growing list of published papers identifying mutations in these genes. As the costs associated with sequencing continue to fall, whole-genome sequencing will probably replace whole-exome sequencing. However, the ability to make sense of non-coding variability is still limited. The integration of genotyping data with expression and proteomics' results will be necessary for researchers to fully understand the effects of genetic variability (both coding and non-coding). Recent improvements in the technology available for the analysis of genetic variability have revolutionized the study of many diseases. Hardy and colleagues illustrate how genome-wide strategies, including whole-genome and whole-exome sequencing, have been used to improve our understanding of the pathobiological mechanisms of neurological diseases Over the past five years the field of neurogenetics has yielded a wealth of data that have facilitated a much greater understanding of the aetiology of many neurological diseases. Most of these advances are a result of improvements in technology that have allowed us to determine whole-genome structure and variation and to examine its impact on phenotype in an unprecedented manner. Genome-wide association studies have provided information on how common genetic variability imparts risk for the development of various complex diseases. Moreover, the identification of rare disease-causing mutations have led to the discovery of novel biochemical pathways that are involved in disease pathogensis. Here, we review these advances and discuss how they have changed the approaches being used to study neurological disorders.

Patients infected with severe acute respiratory syndrome coronavirus 2 might have bacterial and fungal superinfections develop. We describe a clinical case of coronavirus disease with pulmonary aspergillosis associated with Bordetella hinzii pneumonia in an immunocompetent patient in France. B. hinzii infections are rare in humans and develop secondary to immunosuppression or debilitating diseases.

Andrew Singleton, Thomas Gasser and colleagues report results of a genome-wide association study of Parkinson's disease among individuals of European ancestry. They find genome-wide significant associations at two loci, SNCA and MAPT , and provide supporting evidence for a new risk locus on 1q32. We performed a genome-wide association study (GWAS) in 1,713 individuals of European ancestry with Parkinson's disease (PD) and 3,978 controls. After replication in 3,361 cases and 4,573 controls, we observed two strong association signals, one in the gene encoding α-synuclein ( SNCA ; rs2736990, OR = 1.23, P = 2.24 × 10 −16 ) and another at the MAPT locus (rs393152, OR = 0.77, P = 1.95 × 10 −16 ). We exchanged data with colleagues performing a GWAS in Japanese PD cases. Association to PD at SNCA was replicated in the Japanese GWAS 1 , confirming this as a major risk locus across populations. We replicated the effect of a new locus detected in the Japanese cohort ( PARK16 , rs823128, OR = 0.66, P = 7.29 × 10 −8 ) and provide supporting evidence that common variation around LRRK2 modulates risk for PD (rs1491923, OR = 1.14, P = 1.55 × 10 −5 ). These data demonstrate an unequivocal role for common genetic variants in the etiology of typical PD and suggest population-specific genetic heterogeneity in this disease.

Alzheimer’s disease is the most common type of dementia, and it is characterized by a decline in memory or other thinking skills. The greatest risk factor for Alzheimer’s disease is advanced age. A recent genome-wide study identified a locus on chromosome 17 associated with the age at onset, and a specific variant in CCL11 is probably responsible for the association. The association of a protective haplotype with a 10-year delay in the onset of Alzheimer’s disease and the identification of a CCL11 variant with possible functional roles in this association might allow the future development of immunomodulators with the potential to halve disease incidence.