Challenges and opportunities for statistical power and biomarker identification arising from rhythmic variation in proteomics.

Time-of-day variation in the molecular profile of biofluids and tissues is a well-described phenomenon, but-especially for proteomics-is rarely considered in terms of the challenges this presents to reproducible biomarker identification. We provide a case study analysis of human circadian and ultradian rhythmicity in proteins, including in the complement and coagulation cascades and apolipoproteins, with PLG, CFAH, ZA2G and ITIH2 demonstrated as rhythmic for the first time. We also show that rhythmicity increases the risk of Type II errors due to the reduction in statistical power from increased variance, and that controlling for rhythmic time-of-day variation improves statistical power and reduces the chances of Type II errors.

Deleterious coding variation associated with autism is consistent across populations, as exemplified by admixed Latin American populations.

The past decade has seen remarkable progress in identifying genes that, when impacted by deleterious coding variation, confer high risk for autism spectrum disorder (ASD), intellectual disability, and other developmental disorders. However, most underlying gene discovery efforts have focused on individuals of European ancestry, limiting insights into genetic risks across diverse populations. To help address this, the Genomics of Autism in Latin American Ancestries Consortium (GALA) was formed, presenting here the largest sequencing study of ASD in Latin American individuals (n>15,000).

Study of the Prevalence of Human Papillomavirus Genotypes in Jeddah, Saudi Arabia.

Human papillomavirus (HPV), a common sexually transmitted infection, includes over 200 types, some linked to genital warts and various cancers, including cervical, anal, penile, and oropharyngeal cancers. In Saudi Arabia, an estimated 10.7 million women aged 15 years and older are at risk of HPV-related cervical cancer.

Photosensitizer spatial heterogeneity and its impact on personalized interstitial photodynamic therapy treatment planning.

Significance: Personalized photodynamic therapy (PDT) treatment planning requires knowledge of the spatial and temporal co-localization of photons, photosensitizers (PSs), and oxygen. The inter- and intra-subject variability in the photosensitizer concentration can lead to suboptimal outcomes using standard treatment plans.

Aim: We aim to quantify the PS spatial variation in tumors and its effect on PDT treatment planning solutions.