Background: Alzheimer’s disease (AD) affects a significant portion of the aging population, presenting a serious challenge due to the limited availability of effective therapies during its progression. The disease advances rapidly, underscoring the need for early diagnosis and the application of preventative measures. Current diagnostic methods for AD are often expensive and invasive, restricting access for the general public. One potential solution is the use of biomarkers, which can facilitate early detection and treatment through objective, non-invasive, and cost-effective evaluations of AD. This review critically investigates the function and role of biofluid biomarkers in detecting AD, with a specific focus on cerebrospinal fluid (CSF), blood-based, and saliva biomarkers. Results: CSF biomarkers have demonstrated potential for accurate diagnosis and valuable prognostic insights, while blood biomarkers offer a minimally invasive and cost-effective approach for diagnosing cognitive issues. However, while current biomarkers for AD show significant potential, none have yet achieved the precision needed to replace expensive PET scans and CSF assays. The lack of a single accurate biomarker underscores the need for further research to identify novel or combined biomarkers to enhance the clinical efficacy of existing diagnostic tests. In this context, artificial intelligence (AI) and deep-learning (DL) tools present promising avenues for improving biomarker analysis and interpretation, enabling more precise and timely diagnoses. Conclusions: Further research is essential to confirm the utility of all AD biomarkers in clinical settings. Combining biomarker data with AI tools offers a promising path toward revolutionizing the personalized characterization and early diagnosis of AD symptoms.

Type 2 diabetes mellitus (T2DM) is a rising public health concern in Qatar. The relationship between lifestyle factors and T2DM represents one of the most significant public health challenges facing modern societies, with particular relevance to the State of Qatar and the broader Gulf Cooperation Council (GCC) region. The Middle East and North Africa (MENA) region currently exhibits some of the highest T2DM prevalence rates globally, with the Gulf states experiencing particularly rapid increases that parallel their accelerated economic development and societal transformation. This increase in T2DM has been brought about by sedentary lifestyle-related obesity and dietary patterns rich in carbohydrates, particularly from traditional and modern convenience foods. Physical inactivity is further lowered by environmental barriers, including extreme heat, and increased screen time, adding to risks of developing T2DM. This paper highlights these lifestyle factors and proposes interventions such as inclusion of low-glycemic, fiber-dense foods, customized exercise interventions, and food labeling policies. Tackling these issues through culturally and environmentally tailored strategies is essential to reducing T2DM prevalence while preserving Qatar’s traditions. This review synthesizes evidence to propose Qatar-specific, climate-adaptive, and culturally aligned strategies not previously emphasized in the T2DM literature, offering a novel framework for future public health interventions.