Unlocking neurological treatment success with biomarker insights

• Biomarkers are defined indicators of physiological states, pathogenic processes, or responses to intervention⁴.
• In neurological disorders, biomarkers aid in distinguishing conditions, monitoring treatment, predicting prognosis, and ensuring safety⁵.
• Noncompliance with medications can result in treatment failure, but biomarkers help monitor drug levels, and predict treatment response^4,7.
• Ethical clarity is crucial for biological sample ownership and informed consent in large-scale biobanks to sefeguard participant rights and privacy⁸.

Neurological disorders: A diverse spectrum with complex pathogenesis

Neurological disorders (NDs) span a range of conditions affecting the central and peripheral nervous systems, impacting both structure and function¹. The global prevalence of NDs is projected to reach 103 million by 2030². These disorders involve progressive loss of neurological function, including dementia, stroke, epilepsy, migraines, brain injuries, and neuroinfections. Notable neurodegenerative disorders include Alzheimer’s disease (AD), Parkinson’s disease (PD) , amyotrophic lateral sclerosis (ALS), Huntington’s disease (HD), and multiple sclerosis (MS)³. Despite the substantial burden, NDs impose on society and individuals alike, their pathogenesis remains incompletely understood¹. Moreover, the invasive nature of brain biopsies poses challenges for definitive diagnosis³. Therefore, biomarkers play a pivotal role in enabling accurate diagnosis, prognosis, and tracking of disease progression³.

Biomarkers: unveiling clues in health and disease

In 1973, the term “biomarker” emerged to denote the presence or absence of biological material⁴. To standardize its usage, the FDA, and the National Institute of Health Joint Leadership Council in 2016 framed the biomarker definition as “a defined characteristic measured to indicate normal biological processes, pathogenic processes, or responses to exposure or intervention”⁴. A biomarker, whether a molecule, gene, characteristic, or process, indicates normal or abnormal physiological states or disease⁵. Ideally, a biomarker should demostrate high reproducibility, a significant signal-to-noise ratio, and dynamic, reliable modification as the clinical condition progresses⁴.

Marking the way: how biomarkers illuminate neurological disorders

NDs such as Parkinson’s and Alzheimer’s are typically progressive, leading to permanent disability². Early detection maybe effective in slowing its progression toward degeneration. Biomarkers play a crucial role in reliably identifying high-risk individuals and objectively assessing disease progression, outperforming clinical measures which are often less accurate². Biomarkers aid in distinguishing between Alzheimer’s disease or Parkinson’s disease and similar clinical syndromes. Thus, elucidating disease pathophysiology, and standardizing the efficacy assessment of novel neurotherapeutic strategies. Consequently, biomarkers hold significant promise in providing invaluable insights for managing patients with neurodegenerative diseases either pre-symptomatically or shortly after detection².

• Disease diagnosis biomarkers:
  Biomarkers play a crucial role in distinguishing neurological disorders from conditions with similar symptoms. This distinction is vital, given the diverse prognosis and treatment responses across diseases. They enhance personalized medicine by improving therapeutic efficacy. For instance, elevated tau and amyloid-beta proteins in cerebrospinal fluid (CSF) or brain imaging aid in diagnosing Alzheimer’s disease^4,5.
  
  In Parkinson’s disease, characterized by dopamine cell loss and alpha-synuclein buildup, alpha-synuclein is detectable in CSF, and imaging assesses brain dopamine function. In multiple sclerosis, biomarkers like neurofilament light chain (NfL) and myelin basic protein in CSF or blood indicate neuronal damage and demyelination extent⁵.
• Treatment response biomarkers:
  These biomarkers monitor treatment responses, guiding clinical management decisions on treatment continuation⁴. In Parkinson’s disease, specific molecular changes indicate medication or intervention effectiveness. Although some biomarkers are linked to PD, predicting treatment response using them is still and area of active research. Alzheimer’s disease, characterized by amyloid-beta plaques and tau protein tangles, can be assessed via CSF measurement or positron emission tomography (PET) imaging for live brain visualization⁵.
• Prognostic biomarker:
  Biomarkers frequently used to assess the likelihood of experiencing a clinical outcome in individuals with a specific illness or medical state⁴. These outcomes can include mortality, disease progression or relapse, and the onset of a new medical condition. Biomarkers like NfL, indicative of neuronal damage, are elevated in the CSF and blood of multiple sclerosis patients, providing insights into disease activity and progression⁵. The number of trinucleotide CAG (Cytosine, Adenine, Guanine) repetitions in Huntington’s disease patients serves as a prognostic biomarker, with higher repetitions correlating with increased disease severity. Additionally, these biomarkers may inform treatment selection, offering insights into treatment safety and guiding decisions regarding patient care, including hospitalization or intensive care unit admission ⁴.
• Safety biomarker:
  Monitoring hepatic, renal, and cardiovascular functions is essential in many therapies to detect toxicity and ensure the safety of the treatment⁴. Safety markers detect or predict toxicity before clinical signs appear, and changes in biomarker levels indicate toxicity⁴. These biomarkers identify patients at risk, preventing initiation of therapies with significant safety concerns. For instance, genetic variations in CYP2D6 enzymes affect response to psychiatric drugs like antipsychotics, altering drug metabolism and potentially enhancing toxicity risk. For the antipsychotic risperidone, the number of active CYP2D6 genes correlates with cardiac toxicity, as patients with one active gene exhibit longer QTc intervals compared to those with two⁴.

Table below presents a compilation of potential biomarkers in neurological disorders³:

Chronic neurological conditions/ neurodegenerative diseases	Pathological traits	Biomarkers
Parkinson’s disease	Lewy bodies and neurites containing α-synuclein aggregates lead to dopaminergic nigrostriatal neuron loss in the substantia nigra pars compacta	α-Synuclein, orexin, caspase-3, TCS, NfL, Aβ42, p-tau, CRP, D3R, 8-OHG, YKL-40, MCP-1, MHPG, GCase, GlcCer, cathepsin D, DJ-1
Alzheimer’s disease	Extracellular aggregates amyloid β (Aβ) plaques, intracellular neurofibrillary tangles (NFTs) of hyperphosphorylated tau protein, and inflammation result in synapse dysfunction, neuronal loss, and brain atrophy	Tau, p-tau, NfL, FABP, A1-42, MCP-1, YKL-40, TREM2, neurogranin, amyloid PET, NSE, VLP-1, HFABP, albumin, GFAP, α -synuclein, t-tau, pT181-tau, pS396-tau
Huntington’s disease	CAG repeat expansion in the huntingtin gene causes progressive degeneration and atrophy of the striatum, resulting in neuronal loss and cell death	mHTT, tau, NFL, NFH, miRNA, TDP-43, NPY, PDE10A, MRI, PET
Multiple sclerosis	Inflammatory lesions form plaques in the brain and spinal cord’s gray and white matter, causing neuronal demyelination, axonal degeneration, and neurological dysfunction	Tau, NFL, NFH, CXCL13, ApoE, MBP, OPN, NCAM1, NGF, CNTF, GFAP, tau, S100B, Ferritin, CD163, YKL-40, Kir4
Frontotemporal dementia	Aberrant tau aggregate accumulation in the brain leads to frontal lobe atrophy.	Aβ42, t-tau, pT181-tau, pS396-tau, NfL
Epilepsy	Neuronal signaling imbalance causes unpredictable, recurrent seizures, leading to neurodegeneration, blood-brain barrier (BBB) damage, and inflammation	NeuN, PV, FJB, GFAP, IBA1, Timm, DCX, IL-1, IL-6, TNF-α, UCH-L1, NSE, MMP-9, S100B

Despite the promising potential of biomarkers in NDs, several challenges persist, including:

• Many biomarkers lack specificity for a single disorder, complicating differentiation between conditions⁵
• A single biomarker may not accurately assess disease progression due to varying stages of severity based on symptom progression. Instead, an array of biomarkers is utilized to validate the seriousness of neurodegenerative diseases³
• Collecting biomarkers often involves invasive procedures such as lumbar punctures, which may not be suitable for all patients⁵
• Standard staining and biopsy methods, requiring considerable time and effort, may be essential for a thorough prognosis³.

Tracking treatment: harnessing biomarkers for medication adherence

Medication adherence is a critical factor in achieving successful treatment outcomes for various medical conditions. Poor adherence to prescribed medications can lead to treatment failure and disease progression. Biomarkers can be used to monitor drug levels, assess drug metabolism, and predict treatment response. For instance, genetic variants in drug-metabolizing enzymes (such as cytochrome P450 enzymes) can impact drug efficacy and toxicity⁶. By genotyping patients, clinicians can identify those who may require dose adjustments or alternative medications. Additionally, novel technologies are being developed to directly measure drug levels in biological fluids. For example, devices can detect drug concentrations in saliva⁷. These real-time measurements allow clinicians to assess adherence and adjust treatment regimens promptly.

Navigating the ethics of biomarker use:

• Efficiency in a biomarker-driven research program: CETP inhibitors:
  Recent analysis of cholesteryl ester transfer protein (CETP) inhibitors highlights the ethical challenge of assessing biomarker-driven research efficiency. Early-phase trials for five CETP inhibitors i.e. anacetrapib, dalcetrapib, evacetrapib, TA-8995, and torcetrapib demonstrated target hit, but in three of five cases, HDL modulation failed to yield clinically significant benefits, resulting in discontinuation. This underscores HDL modulation’s inadequacy as a valid surrogate biomarker for cardiovascular benefits in this class⁸.
• “Banking” of human biological samples:
  Biological sample ownership laws differ between countries. In the United Kingdom, donors have ownership rights over samples in biobanks, except if collected for research. Conversely, in the United States, donors lack ownership rights for research samples. In Canada, while courts haven’t ruled on ownership, donors possess common law rights to access health information⁹.
• Inadequacy in informed consent
  Unprecedented computational power enables large-scale population biobanks and genetic epidemiology studies. However, this context heightens research ethics challenges, complicating individual consent and privacy protection. Large-scale biobanks cannot predict future sample uses, leading to uncertainty during consent. Genetic testing may repurpose non-genetic samples, and the evolving nature of genetic research hinders explicit disclosure to donors. Repeat consent may also intrude on donors’ lives⁹.
• Risks and burdens of blinded enrollment:
  Risk marker–negative individuals in the blinded placebo cohort bear significant burdens, including frequent study visits involving time-consuming procedures like imaging scans, lumbar punctures, and, in certain cases, placebo injections. These individuals, unaware of their results, may mistakenly perceive themselves as risk marker–positive due to study participation (e.g., attributing unrelated health issues to study side effects). Additionally, certain adverse events may inadvertently disclose the subject’s mutation status¹⁰.

Conclusions:

Biomarkers, serving as defined indicators of physiological states, pathogenic processes, or responses to intervention, play critical roles in neurological disorders. Their ability to enable early detection and assess disease progression aids in personalized treatment strategies. However, the ethical and effective implementation of biomarker-driven research presents challenges. While evaluating biomarker efficiency, as seen with CETP inhibitors, it becomes evident that sole reliance on biomarkers for clinical outcomes requires caution. Additionally, ethical considerations surrounding biological sample ownership demand legal clarity. Informed consent within large-scale biobanks and genetic studies poses its own set of challenges, emphasizing the importance of ongoing dialogue to protect participants’ rights and privacy. Transparent communication and robust ethical oversight are vital for safeguarding participants’ well-being and rights, fostering trust, and advancing ethical biomarker-driven research in neurology and beyond.

We strive for error-free medicine in a word that is sometimes all too humans – Michael C. Burgess

References

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