Roadmap and standard operating procedures for biobanking and discovery of neurochemical markers in ALS

Figures & data

Table I. ALS ideal biomarker characteristics.

1. Sensitive and specific for the heterogeneous syndrome of ALS

2. Detectable prior to the onset of significant wasting/weakness

3. Discriminate between clinical phenotypes based on:

a) Upper and lower motor neuron involvement, e.g. PMA and PLS

b) Patterns of regional involvement, e.g. flail arm/leg, PBP

c) Cognitive involvement, i.e. ALS versus ALS-FTD

d) Extremes of survival, i.e. ‘aggressive’ versus ‘benign’ course

4. Able to predict regional involvement and the pattern of spread in advance:

a) Bulbar dysfunction for early gastrostomy

b) Respiratory dysfunction for early NIV (possibly diaphragm pacing)

c) Cognitive impairment

5. Change in a predictable way with disease progression

6. Sensitivity to confidently judge therapeutic response within weeks of challenge

7. Easily accessible and affordable technology

8. Practical to measure in the physically disabled patient

ALS: amyotrophic lateral sclerosis; FTD: frontotemporal dementia: NIV: non-invasive ventilation; PBP: progressive bulbar palsy; PMA: progressive muscular atrophy; PLS: primary lateral sclerosis.

Table II. Categories of biomarker in ALS.

Category	Purpose	Current benchmark	Challenges
Diagnostic	To reduce diagnostic delay (current mean ∼1 year from symptom onset);	Clinical acumen;	Who are the ‘at risk’ population?
	To more rapidly refer patients to neuromuscular specialist;	ALS neurologists in tertiary referral centers probably >97% sensitive and specific, but predominantly as a result of referral delay	Where is the ‘clinical horizon’ in relation to pathogenesis?
	To distinguish ALS from mimic disorders;		The true mimics are not healthy controls, but pure LMN and pure UMN syndromes
	Permit earlier therapeutic intervention
Prognostic	To identify those with poor prognosis who may require earlier intervention or care planning.	Prognostic modeling of survival with clinical parameters	Prognostic modeling based on tertiary referral center data;
	Identify the minority for whom cognitive involvement likely to be significant and intrusive		Need to establish how earlier intervention in ‘aggressive ALS’ might actually be beneficial.
			Those with ALS-FTD often present with early dementia before motor features are apparent
Monitoring	To provide a marker of early therapeutic benefit in clinical trials.	Survival as main endpoint, which requires trials of >200 patients over 12–24 months.	Heterogeneous syndrome of ALS may distort all trial outcome measures due to different efficacy across phenotypes
	Reduce size and duration of studies.	ALSFRS-R and FVC are alternative surrogate endpoints
	Reduce need for placebo arms
Mechanistic	Biomarkers may provide clues to pathogenesis via pathway analysis and thence provide new candidates	Cellular inclusions, e.g. TDP-43 and FUS indicate abnormal RNA processing; may be important in pathogenesis	Distinguishing pathogenic pathways from epi-phenomena

ALS: amyotrophic lateral sclerosis; ALSFRS-R: revised ALS functional rating score;

FTD: frontotemporal dementia; FVC: forced vital capacity. LMN: lower motor neuron; UMN: upper motor neuron.

Figure 1. Roadmap for biomarker discovery, biobanking and implementation of neurochemical markers in ALS.

Table III. Types of control sample in ALS biomarker studies.

Category of control	Advantage	Disadvantage
Healthy	‘Pure’ sample; greater sensitivity; spouses of patients easily available resource	Ethical approval for invasive procedures especially spinal tap, although research experience is reassuring and should be proactively emphasized in IRB/REC applications.
		Age-matching additionally challenging. Possibly reduced specificity
‘Ward traffic’ i.e. as part of routine investigation with additional sampling volume	Availability. Ethical approval and consent easier to obtain as it is part of routine care	Diagnosis may be idiopathic e.g. ‘headache’ or ‘parasthesiae’, with a need for follow-up to categorize later as further information comes to light (and ethical approval in this respect).
		Experience from lumbar drainage in Normal Pressure Hydrocephalus suggests multiple confounds may exist
Other neurodegenerative disorders	Explore specificity of putative markers, especially neuronal. FTD particularly relevant to ALS	Scarcity. Relevance to ALS? Poor clinical diagnostic accuracy
Clinical ‘mimics’ e.g. multifocal motor neuropathy with conduction block (MFMN), Kennedy's syndrome, cervical spondylosis	Value as source for truly diagnostic biomarkers	Scarcity. Limited value in current clinical practice. Mimics may not be neurodegenerative in pathogenesis e.g. MFMN, spondylosis
Neuro-inflammatory diseases	Relatively common. Explore specificity of putative markers, especially glial. May have ‘mimic’ potential e.g. Primary Progressive MS versus PLS	Relevance of primary immune-based conditions to ALS, including age, natural history, treatments?

ALS: amyotrophic lateral sclerosis; FTD: frontotemporal dementia; MFMN: multifocal motor neuropathy with conduction block; MS: multiple sclerosis; PLS: primary lateral sclerosis.

Table IV. Desirable minimum clinical dataset for ALS biomarker studies.

Category	Clinical information
Generic (ALS and controls)	Age Gender Ethnicity Drugs Past medical history. Family history of neurodegenerative disorders (back two generations)
Phenotype (ALS)	Diagnostic certainty (ALS by revised El Escorial criteria plus PLS or PMA), confirmed each time-point. Symptom onset (months/years) Date of diagnosis Site of onset (bulbar, upper/lower limb, respiratory) Regional phenotypes (flail arm, flail leg, progressive bulbar palsy, upper versus lower motor neuron-predominant ALS, cognitive involvement e.g. ALS-FTD)
Evaluation (ALS)	ALSFRS-R Forced Vital Capacity Upper/lower motor neuron involvement Body Mass Index Cognitive assessment e.g. Verbal Fluency Index
Interventions (ALS)	Gastrostomy Non-invasive ventilation Cough-assist device Tracheostomy Date of death (with consideration of stratification of patients according to time of sampling in relation to overall disease course)

ALS: amyotrophic lateral sclerosis; ALSFRS-R: revised ALS functional rating score;

FTD: frontotemporal dementia; PMA: progressive muscular atrophy; PLS: primary lateral sclerosis.

Table V. Strengths and weaknesses among biomarker sources.

Characteristic	Blood^1	CSF	Urine	Saliva	Skin	Muscle
Proximity to CNS pathology	++	+++	+	+	+	+
Less molecular complexity	+	+	++	+++	++	++
Less invasive	++	+	+++	+++	+	+
Practicality of sampling	+++	++	+++	++	+	+
Ease of handling for storage	++	+ ^2	++	+	+	+
Resistance to exogenous drug contamination	+	+++	+	++	++	++
Candidate molecules to date	++	+++	+	+	+	+
Potential for DNA/RNA analysis	+++	+	+	++	+++	+++

+++: highly significant; ++ : significant; +: low significance.

¹Plasma versus serum needs to be specified; serum may have advantages for the stability of some proteins, e.g. immunoglobulins. EDTA sample will be needed for DNA or RNA studies.

²Bloody tap contamination potential and the particular need for rapid centrifugation.

Figure 2. ‘Quantification tree’ showing the most common approaches for proteome profiling in discovery proteomics. SELDI and 2D-DIGE reveal only pattern information in the first instance, but 2D-DIGE (in contrast to SELDI) can be readily interfaced to mass spectrometric protein identification. MS-based approaches, which reveal both protein profile and identity, branch into stable isotope labeling-based and label-free techniques. Stable isotopes can be introduced by chemical tagging (e.g. iTRAQ) or by metabolic labeling (e.g. SILAC). SILAC can only be applied as a spike-in version to human material as it requires metabolic labeling of proteins in cell culture. For label-free quantification, peptide intensities are compared within separate LC-MS/MS runs.

SELDI: surface-enhanced laser desorption isonization; 2D-DIGE: two-dimensional fluorescence difference gel electrophoresis; MS: mass spectrometry; SILAC: stable isotope labeling with amino acids in cell culture; iTRAQ: isobaric tag for relative and absolute quantitation; LC: liquid chromatography.